Listings Report

Dataset statistics

Number of variables	75
Number of observations	100
Missing cells	843
Missing cells (%)	11.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	58.7 KiB
Average record size in memory	601.3 B

Variable types

Numeric	34
Text	10
Categorical	17
Unsupported	6
DateTime	3
Boolean	5

Alerts

`scrape_id` has constant value ""	Constant
`host_has_profile_pic` has constant value ""	Constant
`amenities` has constant value ""	Constant
`has_availability` has constant value ""	Constant
`calculated_host_listings_count_shared_rooms` has constant value ""	Constant
`source` is highly imbalanced (56.4%)	Imbalance
`host_location` is highly imbalanced (67.5%)	Imbalance
`host_response_rate` is highly imbalanced (56.7%)	Imbalance
`host_verifications` is highly imbalanced (63.1%)	Imbalance
`neighbourhood` is highly imbalanced (60.9%)	Imbalance
`description` has 100 (100.0%) missing values	Missing
`neighborhood_overview` has 43 (43.0%) missing values	Missing
`host_location` has 3 (3.0%) missing values	Missing
`host_about` has 4 (4.0%) missing values	Missing
`host_response_time` has 13 (13.0%) missing values	Missing
`host_response_rate` has 13 (13.0%) missing values	Missing
`host_acceptance_rate` has 16 (16.0%) missing values	Missing
`neighbourhood` has 43 (43.0%) missing values	Missing
`neighbourhood_group_cleansed` has 100 (100.0%) missing values	Missing
`bathrooms` has 100 (100.0%) missing values	Missing
`bedrooms` has 100 (100.0%) missing values	Missing
`price` has 2 (2.0%) missing values	Missing
`calendar_updated` has 100 (100.0%) missing values	Missing
`has_availability` has 2 (2.0%) missing values	Missing
`first_review` has 10 (10.0%) missing values	Missing
`last_review` has 10 (10.0%) missing values	Missing
`review_scores_rating` has 10 (10.0%) missing values	Missing
`review_scores_accuracy` has 10 (10.0%) missing values	Missing
`review_scores_cleanliness` has 10 (10.0%) missing values	Missing
`review_scores_checkin` has 10 (10.0%) missing values	Missing
`review_scores_communication` has 10 (10.0%) missing values	Missing
`review_scores_location` has 10 (10.0%) missing values	Missing
`review_scores_value` has 10 (10.0%) missing values	Missing
`license` has 100 (100.0%) missing values	Missing
`reviews_per_month` has 10 (10.0%) missing values	Missing
`id` has unique values	Unique
`listing_url` has unique values	Unique
`picture_url` has unique values	Unique
`description` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`neighbourhood_group_cleansed` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`bathrooms` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`bedrooms` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`calendar_updated` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`license` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`availability_30` has 25 (25.0%) zeros	Zeros
`availability_60` has 20 (20.0%) zeros	Zeros
`availability_90` has 19 (19.0%) zeros	Zeros
`availability_365` has 12 (12.0%) zeros	Zeros
`number_of_reviews` has 10 (10.0%) zeros	Zeros
`number_of_reviews_ltm` has 31 (31.0%) zeros	Zeros
`number_of_reviews_l30d` has 64 (64.0%) zeros	Zeros
`calculated_host_listings_count_entire_homes` has 18 (18.0%) zeros	Zeros
`calculated_host_listings_count_private_rooms` has 68 (68.0%) zeros	Zeros

Reproduction

Analysis started	2024-04-28 18:03:51.205351
Analysis finished	2024-04-28 18:05:42.733410
Duration	1 minute and 51.53 seconds
Software version	ydata-profiling vv4.7.0
Download configuration	config.json

id
Real number (ℝ)

UNIQUE

Distinct	100
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	225008.94

Minimum	17878
Maximum	404674
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	17878
5-th percentile	48871.2
Q1	88717.75
median	249039.5
Q3	334104.25
95-th percentile	391856.6
Maximum	404674
Range	386796
Interquartile range (IQR)	245386.5

Descriptive statistics

Standard deviation	121200.16
Coefficient of variation (CV)	0.53864598
Kurtosis	-1.419796
Mean	225008.94
Median Absolute Deviation (MAD)	101484.5
Skewness	-0.26980255
Sum	22500894
Variance	1.4689479 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17878	1	1.0%
87762	1	1.0%
262466	1	1.0%
361569	1	1.0%
88781	1	1.0%
361568	1	1.0%
360877	1	1.0%
257618	1	1.0%
256323	1	1.0%
88528	1	1.0%
Other values (90)	90	90.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
17878	1	1.0%
25026	1	1.0%
35764	1	1.0%
41198	1	1.0%
48305	1	1.0%
48901	1	1.0%
49179	1	1.0%
50759	1	1.0%
51703	1	1.0%
53533	1	1.0%

Value	Count	Frequency (%)
404674	1	1.0%
400326	1	1.0%
399476	1	1.0%
396849	1	1.0%
392267	1	1.0%
391835	1	1.0%
380887	1	1.0%
371950	1	1.0%
368146	1	1.0%
361569	1	1.0%

listing_url
Text

UNIQUE

Distinct	100
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	35
Median length	35
Mean length	34.66
Min length	34

Characters and Unicode

Total characters	3466
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	100 ?
Unique (%)	100.0%

Sample

1st row	https://www.airbnb.com/rooms/17878
2nd row	https://www.airbnb.com/rooms/25026
3rd row	https://www.airbnb.com/rooms/35764
4th row	https://www.airbnb.com/rooms/41198
5th row	https://www.airbnb.com/rooms/326205

Value	Count	Frequency (%)
https://www.airbnb.com/rooms/17878	1	1.0%
https://www.airbnb.com/rooms/220705	1	1.0%
https://www.airbnb.com/rooms/35764	1	1.0%
https://www.airbnb.com/rooms/41198	1	1.0%
https://www.airbnb.com/rooms/326205	1	1.0%
https://www.airbnb.com/rooms/326575	1	1.0%
https://www.airbnb.com/rooms/216461	1	1.0%
https://www.airbnb.com/rooms/48305	1	1.0%
https://www.airbnb.com/rooms/216700	1	1.0%
https://www.airbnb.com/rooms/219250	1	1.0%
Other values (90)	90	90.0%

Most occurring characters

Value	Count	Frequency (%)
/	400	11.5%
o	300	8.7%
w	300	8.7%
b	200	5.8%
m	200	5.8%
s	200	5.8%
.	200	5.8%
t	200	5.8%
r	200	5.8%
h	100	2.9%
Other values (16)	1166	33.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3466	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	400	11.5%
o	300	8.7%
w	300	8.7%
b	200	5.8%
m	200	5.8%
s	200	5.8%
.	200	5.8%
t	200	5.8%
r	200	5.8%
h	100	2.9%
Other values (16)	1166	33.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3466	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	400	11.5%
o	300	8.7%
w	300	8.7%
b	200	5.8%
m	200	5.8%
s	200	5.8%
.	200	5.8%
t	200	5.8%
r	200	5.8%
h	100	2.9%
Other values (16)	1166	33.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3466	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	400	11.5%
o	300	8.7%
w	300	8.7%
b	200	5.8%
m	200	5.8%
s	200	5.8%
.	200	5.8%
t	200	5.8%
r	200	5.8%
h	100	2.9%
Other values (16)	1166	33.6%

scrape_id
Categorical

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

20231226034138	100

Length

Max length	14
Median length	14
Mean length	14
Min length	14

Characters and Unicode

Total characters	1400
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	20231226034138
2nd row	20231226034138
3rd row	20231226034138
4th row	20231226034138
5th row	20231226034138

Common Values

Value	Count	Frequency (%)
20231226034138	100	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
20231226034138	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	400	28.6%
3	300	21.4%
0	200	14.3%
1	200	14.3%
6	100	7.1%
4	100	7.1%
8	100	7.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1400	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	400	28.6%
3	300	21.4%
0	200	14.3%
1	200	14.3%
6	100	7.1%
4	100	7.1%
8	100	7.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1400	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	400	28.6%
3	300	21.4%
0	200	14.3%
1	200	14.3%
6	100	7.1%
4	100	7.1%
8	100	7.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1400	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	400	28.6%
3	300	21.4%
0	200	14.3%
1	200	14.3%
6	100	7.1%
4	100	7.1%
8	100	7.1%

last_scraped
Categorical

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

2023-12-27	40
2023-12-26	34
2023-12-28	17
2023-12-30	8
2023-12-29	1

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	1000
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2023-12-27
2nd row	2023-12-27
3rd row	2023-12-27
4th row	2023-12-27
5th row	2023-12-27

Common Values

Value	Count	Frequency (%)
2023-12-27	40	40.0%
2023-12-26	34	34.0%
2023-12-28	17	17.0%
2023-12-30	8	8.0%
2023-12-29	1	1.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2023-12-27	40	40.0%
2023-12-26	34	34.0%
2023-12-28	17	17.0%
2023-12-30	8	8.0%
2023-12-29	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

source
Categorical

IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

city scrape	91
previous scrape	9

Length

Max length	15
Median length	11
Mean length	11.36
Min length	11

Characters and Unicode

Total characters	1136
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	city scrape
2nd row	city scrape
3rd row	city scrape
4th row	city scrape
5th row	city scrape

Common Values

Value	Count	Frequency (%)
city scrape	91	91.0%
previous scrape	9	9.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
scrape	100	50.0%
city	91	45.5%
previous	9	4.5%

Most occurring characters

Value	Count	Frequency (%)
c	191	16.8%
s	109	9.6%
r	109	9.6%
p	109	9.6%
e	109	9.6%
i	100	8.8%
	100	8.8%
a	100	8.8%
t	91	8.0%
y	91	8.0%
Other values (3)	27	2.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1136	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
c	191	16.8%
s	109	9.6%
r	109	9.6%
p	109	9.6%
e	109	9.6%
i	100	8.8%
	100	8.8%
a	100	8.8%
t	91	8.0%
y	91	8.0%
Other values (3)	27	2.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1136	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
c	191	16.8%
s	109	9.6%
r	109	9.6%
p	109	9.6%
e	109	9.6%
i	100	8.8%
	100	8.8%
a	100	8.8%
t	91	8.0%
y	91	8.0%
Other values (3)	27	2.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1136	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
c	191	16.8%
s	109	9.6%
r	109	9.6%
p	109	9.6%
e	109	9.6%
i	100	8.8%
	100	8.8%
a	100	8.8%
t	91	8.0%
y	91	8.0%
Other values (3)	27	2.4%

name
Text

Distinct	97
Distinct (%)	97.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	83
Median length	71
Mean length	64.85
Min length	42

Characters and Unicode

Total characters	6485
Distinct characters	45
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	94 ?
Unique (%)	94.0%

Sample

1st row	Condo in Rio de Janeiro · ★4.70 · 2 bedrooms · 2 beds · 1 bath
2nd row	Rental unit in Rio de Janeiro · ★4.72 · 1 bedroom · 1 bed · 1 bath
3rd row	Loft in Rio de Janeiro · ★4.90 · 1 bedroom · 1 bed · 1.5 baths
4th row	Rental unit in Rio de Janeiro · ★4.21 · 2 bedrooms · 1 bath
5th row	Condo in Rio de Janeiro · ★4.57 · 1 bedroom · 1 bed · 1 bath

Value	Count	Frequency (%)
·	385	23.6%
1	163	10.0%
in	100	6.1%
rio	96	5.9%
de	90	5.5%
janeiro	90	5.5%
unit	72	4.4%
rental	72	4.4%
bedroom	62	3.8%
bath	61	3.7%
Other values (78)	442	27.1%

Most occurring characters

Value	Count	Frequency (%)
	1535	23.7%
e	481	7.4%
o	417	6.4%
·	385	5.9%
i	372	5.7%
n	350	5.4%
d	309	4.8%
b	293	4.5%
a	287	4.4%
t	267	4.1%
Other values (35)	1789	27.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6485	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	1535	23.7%
e	481	7.4%
o	417	6.4%
·	385	5.9%
i	372	5.7%
n	350	5.4%
d	309	4.8%
b	293	4.5%
a	287	4.4%
t	267	4.1%
Other values (35)	1789	27.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6485	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	1535	23.7%
e	481	7.4%
o	417	6.4%
·	385	5.9%
i	372	5.7%
n	350	5.4%
d	309	4.8%
b	293	4.5%
a	287	4.4%
t	267	4.1%
Other values (35)	1789	27.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6485	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	1535	23.7%
e	481	7.4%
o	417	6.4%
·	385	5.9%
i	372	5.7%
n	350	5.4%
d	309	4.8%
b	293	4.5%
a	287	4.4%
t	267	4.1%
Other values (35)	1789	27.6%

description
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

neighborhood_overview
Text

MISSING

Distinct	57
Distinct (%)	100.0%
Missing	43
Missing (%)	43.0%
Memory size	932.0 B

Length

Max length	1000
Median length	279
Mean length	377.98246
Min length	30

Characters and Unicode

Total characters	21545
Distinct characters	98
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	57 ?
Unique (%)	100.0%

Sample

1st row	This is the one of the bests spots in Rio. Because of the large balcony and proximity to the beach, it has huge advantages in the current situation.
2nd row	Copacabana is a lively neighborhood and the apartment is located very close to an area in Copa full of bars, cafes and restaurants at Rua Bolivar and Domingos Ferreira. Copacabana never sleeps, there is always movement and it's a great mix of all kinds of people.
3rd row	Our guests will experience living with a local peole "Carioca" in a very friendly building with 24 hours a day security with all kind of stores, banks, transports, restaurants.
4th row	Come to stay in Baixo Copa, the more trendy and happy neighborhood of all Rio de Janeiro, in the heart of Copacabana, less than a half block from the beach. Restaurants, bars, grocery stores, theaters, banks, hotels and tourism agencies are in the neighborhood.
5th row	Enter Bossa Nova history by staying in the very street where real-life 'Girl From Ipanema' inspired Vinicius de Moraes to write the worldwide famous song, "each day when she walks to the sea".<br /><br />Located seconds from Ipanema Beach's best spot Posto 9, on the first beach block in the heart of Ipanema’s very best neighbourhood, enjoy staying in this elegant and modern hideaway in a peaceful residential street.<br /><br />Ipanema and Leblon are by far the safest locations in Rio, with popular restaurants, cafes and boutique stores walking distance to the apartment.

Value	Count	Frequency (%)
the	175	4.9%
and	113	3.2%
to	77	2.2%
a	75	2.1%
of	68	1.9%
de	60	1.7%
in	56	1.6%
is	55	1.6%
e	53	1.5%
br	41	1.2%
Other values (1271)	2773	78.2%

Most occurring characters

Value	Count	Frequency (%)
	3528	16.4%
a	1866	8.7%
e	1828	8.5%
o	1397	6.5%
t	1293	6.0%
r	1263	5.9%
s	1116	5.2%
i	1111	5.2%
n	1010	4.7%
d	616	2.9%
Other values (88)	6517	30.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	21545	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	3528	16.4%
a	1866	8.7%
e	1828	8.5%
o	1397	6.5%
t	1293	6.0%
r	1263	5.9%
s	1116	5.2%
i	1111	5.2%
n	1010	4.7%
d	616	2.9%
Other values (88)	6517	30.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	21545	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	3528	16.4%
a	1866	8.7%
e	1828	8.5%
o	1397	6.5%
t	1293	6.0%
r	1263	5.9%
s	1116	5.2%
i	1111	5.2%
n	1010	4.7%
d	616	2.9%
Other values (88)	6517	30.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	21545	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	3528	16.4%
a	1866	8.7%
e	1828	8.5%
o	1397	6.5%
t	1293	6.0%
r	1263	5.9%
s	1116	5.2%
i	1111	5.2%
n	1010	4.7%
d	616	2.9%
Other values (88)	6517	30.2%

picture_url
Text

UNIQUE

Distinct	100
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	110
Median length	109
Mean length	71.84
Min length	61

Characters and Unicode

Total characters	7184
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	100 ?
Unique (%)	100.0%

Sample

1st row	https://a0.muscache.com/pictures/65320518/30698f38_original.jpg
2nd row	https://a0.muscache.com/pictures/a745aa21-b8dd-4959-a040-eb8e6e6f07ee.jpg
3rd row	https://a0.muscache.com/pictures/23782972/1d3e55b0_original.jpg
4th row	https://a0.muscache.com/pictures/3576716/2d6a9301_original.jpg
5th row	https://a0.muscache.com/pictures/c550151d-910c-40c6-96a8-d2a8bd770361.jpg

Value	Count	Frequency (%)
https://a0.muscache.com/pictures/65320518/30698f38_original.jpg	1	1.0%
https://a0.muscache.com/pictures/d0fc79d7-bb33-47fa-bfea-f4ca92956b79.jpg	1	1.0%
https://a0.muscache.com/pictures/23782972/1d3e55b0_original.jpg	1	1.0%
https://a0.muscache.com/pictures/3576716/2d6a9301_original.jpg	1	1.0%
https://a0.muscache.com/pictures/c550151d-910c-40c6-96a8-d2a8bd770361.jpg	1	1.0%
https://a0.muscache.com/pictures/4cffcbcf-16c2-4624-afee-29a7ffe20698.jpg	1	1.0%
https://a0.muscache.com/pictures/2628485/1ed768bb_original.jpg	1	1.0%
https://a0.muscache.com/pictures/miso/hosting-48305/original/cce14bf9-c5b6-44c6-a89f-61323975afdb.jpeg	1	1.0%
https://a0.muscache.com/pictures/6162310/be07750f_original.jpg	1	1.0%
https://a0.muscache.com/pictures/60226390/d079690d_original.jpg	1	1.0%
Other values (90)	90	90.0%

Most occurring characters

Value	Count	Frequency (%)
c	510	7.1%
/	501	7.0%
a	390	5.4%
e	336	4.7%
s	328	4.6%
t	320	4.5%
p	310	4.3%
.	300	4.2%
i	272	3.8%
0	262	3.6%
Other values (26)	3655	50.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7184	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
c	510	7.1%
/	501	7.0%
a	390	5.4%
e	336	4.7%
s	328	4.6%
t	320	4.5%
p	310	4.3%
.	300	4.2%
i	272	3.8%
0	262	3.6%
Other values (26)	3655	50.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7184	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
c	510	7.1%
/	501	7.0%
a	390	5.4%
e	336	4.7%
s	328	4.6%
t	320	4.5%
p	310	4.3%
.	300	4.2%
i	272	3.8%
0	262	3.6%
Other values (26)	3655	50.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7184	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
c	510	7.1%
/	501	7.0%
a	390	5.4%
e	336	4.7%
s	328	4.6%
t	320	4.5%
p	310	4.3%
.	300	4.2%
i	272	3.8%
0	262	3.6%
Other values (26)	3655	50.9%

host_id
Real number (ℝ)

Distinct	88
Distinct (%)	88.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	979632.26

Minimum	68997
Maximum	7506316
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	68997
5-th percentile	109643.9
Q1	406904.5
median	798441
Q3	1418424.8
95-th percentile	1962093.5
Maximum	7506316
Range	7437319
Interquartile range (IQR)	1011520.2

Descriptive statistics

Standard deviation	907412.4
Coefficient of variation (CV)	0.9262786
Kurtosis	26.054933
Mean	979632.26
Median Absolute Deviation (MAD)	516924.5
Skewness	3.8534002
Sum	97963226
Variance	8.2339727 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
474221	3	3.0%
406989	3	3.0%
829630	2	2.0%
1603206	2	2.0%
1858602	2	2.0%
1298591	2	2.0%
70933	2	2.0%
235496	2	2.0%
1172595	2	2.0%
1207700	2	2.0%
Other values (78)	78	78.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
68997	1	1.0%
70933	2	2.0%
93005	1	1.0%
102840	1	1.0%
110002	1	1.0%
132230	1	1.0%
153691	1	1.0%
178975	1	1.0%
222884	1	1.0%
224192	1	1.0%

Value	Count	Frequency (%)
7506316	1	1.0%
2537111	1	1.0%
1998370	1	1.0%
1994382	1	1.0%
1982737	1	1.0%
1961007	1	1.0%
1910409	1	1.0%
1858602	2	2.0%
1824379	1	1.0%
1809627	1	1.0%

host_url
Text

Distinct	88
Distinct (%)	88.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	41
Median length	40
Mean length	40.43
Min length	39

Characters and Unicode

Total characters	4043
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	78 ?
Unique (%)	78.0%

Sample

1st row	https://www.airbnb.com/users/show/68997
2nd row	https://www.airbnb.com/users/show/102840
3rd row	https://www.airbnb.com/users/show/153691
4th row	https://www.airbnb.com/users/show/178975
5th row	https://www.airbnb.com/users/show/1603206

Value	Count	Frequency (%)
https://www.airbnb.com/users/show/474221	3	3.0%
https://www.airbnb.com/users/show/406989	3	3.0%
https://www.airbnb.com/users/show/70933	2	2.0%
https://www.airbnb.com/users/show/1172595	2	2.0%
https://www.airbnb.com/users/show/235496	2	2.0%
https://www.airbnb.com/users/show/1207700	2	2.0%
https://www.airbnb.com/users/show/1298591	2	2.0%
https://www.airbnb.com/users/show/1858602	2	2.0%
https://www.airbnb.com/users/show/1603206	2	2.0%
https://www.airbnb.com/users/show/829630	2	2.0%
Other values (78)	78	78.0%

Most occurring characters

Value	Count	Frequency (%)
/	500	12.4%
s	400	9.9%
w	400	9.9%
h	200	4.9%
r	200	4.9%
t	200	4.9%
b	200	4.9%
o	200	4.9%
.	200	4.9%
1	109	2.7%
Other values (18)	1434	35.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4043	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	500	12.4%
s	400	9.9%
w	400	9.9%
h	200	4.9%
r	200	4.9%
t	200	4.9%
b	200	4.9%
o	200	4.9%
.	200	4.9%
1	109	2.7%
Other values (18)	1434	35.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4043	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	500	12.4%
s	400	9.9%
w	400	9.9%
h	200	4.9%
r	200	4.9%
t	200	4.9%
b	200	4.9%
o	200	4.9%
.	200	4.9%
1	109	2.7%
Other values (18)	1434	35.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4043	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	500	12.4%
s	400	9.9%
w	400	9.9%
h	200	4.9%
r	200	4.9%
t	200	4.9%
b	200	4.9%
o	200	4.9%
.	200	4.9%
1	109	2.7%
Other values (18)	1434	35.5%

host_name
Text

Distinct	83
Distinct (%)	83.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	24
Median length	16
Mean length	7.46
Min length	3

Characters and Unicode

Total characters	746
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	70 ?
Unique (%)	70.0%

Sample

1st row	Matthias
2nd row	Viviane
3rd row	Patricia Miranda & Paulo
4th row	Nicky
5th row	Bob

Value	Count	Frequency (%)
maria	5	3.8%
	5	3.8%
casa	4	3.0%
silvia	3	2.3%
bob	3	2.3%
48	3	2.3%
guesthouse	3	2.3%
ricardo	3	2.3%
june	3	2.3%
da	2	1.5%
Other values (89)	98	74.2%

Most occurring characters

Value	Count	Frequency (%)
a	129	17.3%
i	71	9.5%
r	51	6.8%
e	51	6.8%
n	40	5.4%
o	40	5.4%
l	35	4.7%
	33	4.4%
s	29	3.9%
u	20	2.7%
Other values (46)	247	33.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	746	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	129	17.3%
i	71	9.5%
r	51	6.8%
e	51	6.8%
n	40	5.4%
o	40	5.4%
l	35	4.7%
	33	4.4%
s	29	3.9%
u	20	2.7%
Other values (46)	247	33.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	746	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	129	17.3%
i	71	9.5%
r	51	6.8%
e	51	6.8%
n	40	5.4%
o	40	5.4%
l	35	4.7%
	33	4.4%
s	29	3.9%
u	20	2.7%
Other values (46)	247	33.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	746	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	129	17.3%
i	71	9.5%
r	51	6.8%
e	51	6.8%
n	40	5.4%
o	40	5.4%
l	35	4.7%
	33	4.4%
s	29	3.9%
u	20	2.7%
Other values (46)	247	33.1%

host_since
Date

Distinct	81
Distinct (%)	81.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Minimum	2010-01-08 00:00:00
Maximum	2013-07-15 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

host_location
Categorical

IMBALANCE MISSING

Distinct	12
Distinct (%)	12.4%
Missing	3
Missing (%)	3.0%
Memory size	932.0 B

Rio de Janeiro, Brazil	81
Brazil	5
State of Rio de Janeiro, Brazil	2
Rio, Brazil	1
Mesa, AZ	1
Other values (7)	7

Length

Max length	31
Median length	22
Mean length	20.639175
Min length	6

Characters and Unicode

Total characters	2002
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	9 ?
Unique (%)	9.3%

Sample

1st row	Rio de Janeiro, Brazil
2nd row	Rio de Janeiro, Brazil
3rd row	Rio de Janeiro, Brazil
4th row	Rio de Janeiro, Brazil
5th row	Rio de Janeiro, Brazil

Common Values

Value	Count	Frequency (%)
Rio de Janeiro, Brazil	81	81.0%
Brazil	5	5.0%
State of Rio de Janeiro, Brazil	2	2.0%
Rio, Brazil	1	1.0%
Mesa, AZ	1	1.0%
San Diego, CA	1	1.0%
Florianópolis, Brazil	1	1.0%
Sao Paulo, Brazil	1	1.0%
Berlin, Germany	1	1.0%
Miami Beach, FL	1	1.0%
Other values (2)	2	2.0%
(Missing)	3	3.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
brazil	91	25.1%
rio	84	23.2%
janeiro	83	22.9%
de	83	22.9%
state	2	0.6%
of	2	0.6%
berlin	1	0.3%
zug	1	0.3%
spain	1	0.3%
palma	1	0.3%
Other values (13)	13	3.6%

Most occurring characters

Value	Count	Frequency (%)
i	266	13.3%
	265	13.2%
a	188	9.4%
r	178	8.9%
o	174	8.7%
e	174	8.7%
l	97	4.8%
B	93	4.6%
z	92	4.6%
,	92	4.6%
Other values (26)	383	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2002	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	266	13.3%
	265	13.2%
a	188	9.4%
r	178	8.9%
o	174	8.7%
e	174	8.7%
l	97	4.8%
B	93	4.6%
z	92	4.6%
,	92	4.6%
Other values (26)	383	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2002	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	266	13.3%
	265	13.2%
a	188	9.4%
r	178	8.9%
o	174	8.7%
e	174	8.7%
l	97	4.8%
B	93	4.6%
z	92	4.6%
,	92	4.6%
Other values (26)	383	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2002	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	266	13.3%
	265	13.2%
a	188	9.4%
r	178	8.9%
o	174	8.7%
e	174	8.7%
l	97	4.8%
B	93	4.6%
z	92	4.6%
,	92	4.6%
Other values (26)	383	19.1%

host_about
Text

MISSING

Distinct	84
Distinct (%)	87.5%
Missing	4
Missing (%)	4.0%
Memory size	932.0 B

Length

Max length	3837
Median length	405
Mean length	492.80208
Min length	63

Characters and Unicode

Total characters	47309
Distinct characters	111
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	74 ?
Unique (%)	77.1%

Sample

1st row	I am a journalist/writer. Lived in NYC for 15 years. I am now based in Rio and published 3 volumes of travel stories on AMAZ0N: "The World Is My Oyster". If you have never been to Rio, check out the first story, and you'll get an idea. Apart from Rio, you'll find 29 other travel stories from all around the globe.
2nd row	Hi guys, Viviane is a commercial photographer, an avid world traveler, (a former photographer for Airbnb) and an Airbnb superhost. And a free lance photographer for other wonderful clients. She loves life and meeting people. We work together in providing the best accommodation to people and we are firm believers of enjoying the moment as a prime attitude towards life!
3rd row	Hello, We are Patricia Miranda and Paulo. We are a couple who love to meet new people, new cultures, we both are very easy going persons, We are retired after working for several years in tourism and an international airline company. We also used do host in our own residence International students from all over the world. We are gay friendly and everybody is welcome! !
4th row	Hi fellow Airbnb-ers, Mr Francis , Nixx, Nicky ,Nick call me what you like Originally from England but now in South America I love This crazy thing called life. I enjoy meeting interesting multi dimensional people from any country, class or colour ., I don't understand negative or petty people! because I believe life is just too short! I'm not the greatest tour guide, but it would be my pleasure to help you where I can. I administrate a few places on here, so feel free to take a browse of my listings. Please remember that some of these places may be owners homes and not hotels, So don't expect the hilton treatment as I like to keep it sweet & simple. Let me know also if the apt is different from what was listed and I will do my best to Rectify the situation. Remember even though we are here to do a lil Bizniz the most important thing is to enjoy Rio de Janeiro in all it's splendour ! Rio is always an Experience! My favourite travel hotspots outside of Brazil - Colombia or Caribbean Here is a story for you There was a married American guy called Lance who was working abroad as a computer systems analyst to make ends meet.He traveled a lot for his job And had been doing so for the last 37 years. Last year whilst working in Thailand He picked up a young sexy wife 23 years old she was and a real beauty! It was really difficult for him to leave her at home, but the bills needed to be paid and besides his wife was high maintenance. In a particularly difficult month he received a message from his Desirable Wife who was taking care of his home" I signed up for a new service Airbnb Where you can rent space in your house,make good money and I buy new Shoes" Having a beautiful home (and not to mention photo), it wasn't long before she received A guest, actually a handsome pilot from Greece, Adonis was his name. After 5 days Lance could hardly make contact with his wife but unexpectedly received a message from his Airbnb guest. : Hi Sir, Thank you, I enjoyed using your home & everything your city had to offer, I hope you won't be mad but I was using your wife...I was using day and night ... I explored immensely, I was using when you are not present at home... In fact I was using more than You are using..... I confess this because now I feel very much guilt... And is not acceptable under the eyes of God Hope You will accept my sincere apologies". ... Lance distraught with this revelation , jumped On the next plane to his city, , entered his home tied & taped up his wife., and made her watch while he cut Up and burnt all her expensive clothes and shoes, put her in front of the mirror And proceeded to shear off her hair Few minutes later he received another message : Sorry sir, spelling mistake ... wifi not wife. Lol!
5th row	I'm originally from the US, but moved to this Great City of Rio de Janeiro.

Value	Count	Frequency (%)
and	240	2.9%
e	185	2.3%
the	183	2.2%
a	182	2.2%
de	180	2.2%
to	179	2.2%
i	148	1.8%
in	135	1.6%
	110	1.3%
rio	110	1.3%
Other values (2166)	6547	79.9%

Most occurring characters

Value	Count	Frequency (%)
	8343	17.6%
e	4312	9.1%
a	3847	8.1%
o	3214	6.8%
i	2613	5.5%
r	2313	4.9%
n	2312	4.9%
s	2304	4.9%
t	2303	4.9%
d	1482	3.1%
Other values (101)	14266	30.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	47309	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	8343	17.6%
e	4312	9.1%
a	3847	8.1%
o	3214	6.8%
i	2613	5.5%
r	2313	4.9%
n	2312	4.9%
s	2304	4.9%
t	2303	4.9%
d	1482	3.1%
Other values (101)	14266	30.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	47309	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	8343	17.6%
e	4312	9.1%
a	3847	8.1%
o	3214	6.8%
i	2613	5.5%
r	2313	4.9%
n	2312	4.9%
s	2304	4.9%
t	2303	4.9%
d	1482	3.1%
Other values (101)	14266	30.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	47309	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	8343	17.6%
e	4312	9.1%
a	3847	8.1%
o	3214	6.8%
i	2613	5.5%
r	2313	4.9%
n	2312	4.9%
s	2304	4.9%
t	2303	4.9%
d	1482	3.1%
Other values (101)	14266	30.2%

host_response_time
Categorical

MISSING

Distinct	4
Distinct (%)	4.6%
Missing	13
Missing (%)	13.0%
Memory size	932.0 B

within an hour	47
within a few hours	29
within a day	6
a few days or more	5

Length

Max length	18
Median length	14
Mean length	15.425287
Min length	12

Characters and Unicode

Total characters	1342
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	within an hour
2nd row	within an hour
3rd row	within an hour
4th row	within an hour
5th row	within a few hours

Common Values

Value	Count	Frequency (%)
within an hour	47	47.0%
within a few hours	29	29.0%
within a day	6	6.0%
a few days or more	5	5.0%
(Missing)	13	13.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
within	82	27.3%
an	47	15.7%
hour	47	15.7%
a	40	13.3%
few	34	11.3%
hours	29	9.7%
day	6	2.0%
days	5	1.7%
or	5	1.7%
more	5	1.7%

Most occurring characters

Value	Count	Frequency (%)
	213	15.9%
i	164	12.2%
h	158	11.8%
n	129	9.6%
w	116	8.6%
a	98	7.3%
o	86	6.4%
r	86	6.4%
t	82	6.1%
u	76	5.7%
Other values (6)	134	10.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1342	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	213	15.9%
i	164	12.2%
h	158	11.8%
n	129	9.6%
w	116	8.6%
a	98	7.3%
o	86	6.4%
r	86	6.4%
t	82	6.1%
u	76	5.7%
Other values (6)	134	10.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1342	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	213	15.9%
i	164	12.2%
h	158	11.8%
n	129	9.6%
w	116	8.6%
a	98	7.3%
o	86	6.4%
r	86	6.4%
t	82	6.1%
u	76	5.7%
Other values (6)	134	10.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1342	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	213	15.9%
i	164	12.2%
h	158	11.8%
n	129	9.6%
w	116	8.6%
a	98	7.3%
o	86	6.4%
r	86	6.4%
t	82	6.1%
u	76	5.7%
Other values (6)	134	10.0%

host_response_rate
Categorical

IMBALANCE MISSING

Distinct	9
Distinct (%)	10.3%
Missing	13
Missing (%)	13.0%
Memory size	932.0 B

100%	66
90%	9
0%	5
50%	2
96%	1
Other values (4)	4

Length

Max length	4
Median length	4
Mean length	3.7011494
Min length	2

Characters and Unicode

Total characters	322
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	5.7%

Sample

1st row	100%
2nd row	100%
3rd row	100%
4th row	90%
5th row	100%

Common Values

Value	Count	Frequency (%)
100%	66	66.0%
90%	9	9.0%
0%	5	5.0%
50%	2	2.0%
96%	1	1.0%
70%	1	1.0%
63%	1	1.0%
80%	1	1.0%
99%	1	1.0%
(Missing)	13	13.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
100	66	75.9%
90	9	10.3%
0	5	5.7%
50	2	2.3%
96	1	1.1%
70	1	1.1%
63	1	1.1%
80	1	1.1%
99	1	1.1%

Most occurring characters

Value	Count	Frequency (%)
0	150	46.6%
%	87	27.0%
1	66	20.5%
9	12	3.7%
5	2	0.6%
6	2	0.6%
7	1	0.3%
3	1	0.3%
8	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	322	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	150	46.6%
%	87	27.0%
1	66	20.5%
9	12	3.7%
5	2	0.6%
6	2	0.6%
7	1	0.3%
3	1	0.3%
8	1	0.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	322	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	150	46.6%
%	87	27.0%
1	66	20.5%
9	12	3.7%
5	2	0.6%
6	2	0.6%
7	1	0.3%
3	1	0.3%
8	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	322	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	150	46.6%
%	87	27.0%
1	66	20.5%
9	12	3.7%
5	2	0.6%
6	2	0.6%
7	1	0.3%
3	1	0.3%
8	1	0.3%

host_acceptance_rate
Categorical

MISSING

Distinct	32
Distinct (%)	38.1%
Missing	16
Missing (%)	16.0%
Memory size	932.0 B

100%	19
93%	6
0%	5
96%	3
88%	3
Other values (27)	48

Length

Max length	4
Median length	3
Mean length	3.1428571
Min length	2

Characters and Unicode

Total characters	264
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	14 ?
Unique (%)	16.7%

Sample

1st row	96%
2nd row	80%
3rd row	98%
4th row	89%
5th row	93%

Common Values

Value	Count	Frequency (%)
100%	19	19.0%
93%	6	6.0%
0%	5	5.0%
96%	3	3.0%
88%	3	3.0%
83%	3	3.0%
92%	3	3.0%
77%	3	3.0%
95%	3	3.0%
86%	3	3.0%
Other values (22)	33	33.0%
(Missing)	16	16.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
100	19	22.6%
93	6	7.1%
0	5	6.0%
96	3	3.6%
88	3	3.6%
83	3	3.6%
92	3	3.6%
77	3	3.6%
95	3	3.6%
86	3	3.6%
Other values (22)	33	39.3%

Most occurring characters

Value	Count	Frequency (%)
%	84	31.8%
0	46	17.4%
9	32	12.1%
8	25	9.5%
1	22	8.3%
7	15	5.7%
3	10	3.8%
6	10	3.8%
5	9	3.4%
4	6	2.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
%	84	31.8%
0	46	17.4%
9	32	12.1%
8	25	9.5%
1	22	8.3%
7	15	5.7%
3	10	3.8%
6	10	3.8%
5	9	3.4%
4	6	2.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
%	84	31.8%
0	46	17.4%
9	32	12.1%
8	25	9.5%
1	22	8.3%
7	15	5.7%
3	10	3.8%
6	10	3.8%
5	9	3.4%
4	6	2.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
%	84	31.8%
0	46	17.4%
9	32	12.1%
8	25	9.5%
1	22	8.3%
7	15	5.7%
3	10	3.8%
6	10	3.8%
5	9	3.4%
4	6	2.3%

host_is_superhost
Boolean

Distinct	2
Distinct (%)	2.0%
Missing	1
Missing (%)	1.0%
Memory size	332.0 B

False	56
True	43
(Missing)	1

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	56	56.0%
True	43	43.0%
(Missing)	1	1.0%

host_thumbnail_url
Text

Distinct	88
Distinct (%)	88.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	129
Median length	128.5
Mean length	104.65
Min length	99

Characters and Unicode

Total characters	10465
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	78 ?
Unique (%)	78.0%

Sample

1st row	https://a0.muscache.com/im/pictures/user/67b13cea-8c11-49c0-a08d-7f42c330676e.jpg?aki_policy=profile_small
2nd row	https://a0.muscache.com/im/pictures/user/315ddc81-bea3-4bf0-8fc7-be197a6541ff.jpg?aki_policy=profile_small
3rd row	https://a0.muscache.com/im/users/153691/profile_pic/1277774787/original.jpg?aki_policy=profile_small
4th row	https://a0.muscache.com/im/users/178975/profile_pic/1384245754/original.jpg?aki_policy=profile_small
5th row	https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_small

Value	Count	Frequency (%)
https://a0.muscache.com/im/pictures/user/1b75500d-9a03-4d7e-87b7-e578a0773444.jpg?aki_policy=profile_small	3	3.0%
https://a0.muscache.com/im/pictures/user/31fc9c9f-26b4-44d6-bdaa-9f9d5ded347e.jpg?aki_policy=profile_small	3	3.0%
https://a0.muscache.com/im/pictures/user/c2d77835-fab6-45f9-a3ef-ef570dda44a5.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/pictures/user/45ee1619-302f-47cc-8c04-41e8b85278dc.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/pictures/user/user-235496/original/c89b1709-3da6-4618-8b5a-996139275263.jpeg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/users/1207700/profile_pic/1316987019/original.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/users/1298591/profile_pic/1421192290/original.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/users/1858602/profile_pic/1330914215/original.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_small	2	2.0%
https://a0.muscache.com/im/users/829630/profile_pic/1326368431/original.jpg?aki_policy=profile_small	2	2.0%
Other values (78)	78	78.0%

Most occurring characters

Value	Count	Frequency (%)
/	700	6.7%
i	645	6.2%
c	597	5.7%
a	579	5.5%
p	545	5.2%
e	507	4.8%
s	505	4.8%
l	495	4.7%
m	400	3.8%
o	395	3.8%
Other values (29)	5097	48.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	700	6.7%
i	645	6.2%
c	597	5.7%
a	579	5.5%
p	545	5.2%
e	507	4.8%
s	505	4.8%
l	495	4.7%
m	400	3.8%
o	395	3.8%
Other values (29)	5097	48.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	700	6.7%
i	645	6.2%
c	597	5.7%
a	579	5.5%
p	545	5.2%
e	507	4.8%
s	505	4.8%
l	495	4.7%
m	400	3.8%
o	395	3.8%
Other values (29)	5097	48.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	700	6.7%
i	645	6.2%
c	597	5.7%
a	579	5.5%
p	545	5.2%
e	507	4.8%
s	505	4.8%
l	495	4.7%
m	400	3.8%
o	395	3.8%
Other values (29)	5097	48.7%

host_picture_url
Text

Distinct	88
Distinct (%)	88.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Length

Max length	132
Median length	131.5
Mean length	107.65
Min length	102

Characters and Unicode

Total characters	10765
Distinct characters	40
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	78 ?
Unique (%)	78.0%

Sample

1st row	https://a0.muscache.com/im/pictures/user/67b13cea-8c11-49c0-a08d-7f42c330676e.jpg?aki_policy=profile_x_medium
2nd row	https://a0.muscache.com/im/pictures/user/315ddc81-bea3-4bf0-8fc7-be197a6541ff.jpg?aki_policy=profile_x_medium
3rd row	https://a0.muscache.com/im/users/153691/profile_pic/1277774787/original.jpg?aki_policy=profile_x_medium
4th row	https://a0.muscache.com/im/users/178975/profile_pic/1384245754/original.jpg?aki_policy=profile_x_medium
5th row	https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_x_medium

Value	Count	Frequency (%)
https://a0.muscache.com/im/pictures/user/1b75500d-9a03-4d7e-87b7-e578a0773444.jpg?aki_policy=profile_x_medium	3	3.0%
https://a0.muscache.com/im/pictures/user/31fc9c9f-26b4-44d6-bdaa-9f9d5ded347e.jpg?aki_policy=profile_x_medium	3	3.0%
https://a0.muscache.com/im/pictures/user/c2d77835-fab6-45f9-a3ef-ef570dda44a5.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/pictures/user/45ee1619-302f-47cc-8c04-41e8b85278dc.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/pictures/user/user-235496/original/c89b1709-3da6-4618-8b5a-996139275263.jpeg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/users/1207700/profile_pic/1316987019/original.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/users/1298591/profile_pic/1421192290/original.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/users/1858602/profile_pic/1330914215/original.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_x_medium	2	2.0%
https://a0.muscache.com/im/users/829630/profile_pic/1326368431/original.jpg?aki_policy=profile_x_medium	2	2.0%
Other values (78)	78	78.0%

Most occurring characters

Value	Count	Frequency (%)
i	745	6.9%
/	700	6.5%
e	607	5.6%
c	597	5.5%
p	545	5.1%
m	500	4.6%
a	479	4.4%
s	405	3.8%
o	395	3.7%
u	355	3.3%
Other values (30)	5437	50.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	10765	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	745	6.9%
/	700	6.5%
e	607	5.6%
c	597	5.5%
p	545	5.1%
m	500	4.6%
a	479	4.4%
s	405	3.8%
o	395	3.7%
u	355	3.3%
Other values (30)	5437	50.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	10765	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	745	6.9%
/	700	6.5%
e	607	5.6%
c	597	5.5%
p	545	5.1%
m	500	4.6%
a	479	4.4%
s	405	3.8%
o	395	3.7%
u	355	3.3%
Other values (30)	5437	50.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	10765	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	745	6.9%
/	700	6.5%
e	607	5.6%
c	597	5.5%
p	545	5.1%
m	500	4.6%
a	479	4.4%
s	405	3.8%
o	395	3.7%
u	355	3.3%
Other values (30)	5437	50.5%

host_neighbourhood
Categorical

Distinct	17
Distinct (%)	17.2%
Missing	1
Missing (%)	1.0%
Memory size	932.0 B

Copacabana	44
Santa Teresa	10
Ipanema	9
Leblon	7
Barra da Tijuca	6
Other values (12)	23

Length

Max length	24
Median length	15
Mean length	9.5656566
Min length	3

Characters and Unicode

Total characters	947
Distinct characters	35
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	5.1%

Sample

1st row	Copacabana
2nd row	Copacabana
3rd row	Copacabana
4th row	Copacabana
5th row	Copacabana

Common Values

Value	Count	Frequency (%)
Copacabana	44	44.0%
Santa Teresa	10	10.0%
Ipanema	9	9.0%
Leblon	7	7.0%
Barra da Tijuca	6	6.0%
Flamengo	4	4.0%
Botafogo	3	3.0%
Lapa	3	3.0%
Jardin Botânico	2	2.0%
Vidigal	2	2.0%
Other values (7)	9	9.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
copacabana	44	34.6%
teresa	10	7.9%
santa	10	7.9%
ipanema	9	7.1%
leblon	7	5.5%
da	7	5.5%
tijuca	7	5.5%
barra	6	4.7%
flamengo	4	3.1%
botafogo	3	2.4%
Other values (13)	20	15.7%

Most occurring characters

Value	Count	Frequency (%)
a	278	29.4%
n	83	8.8%
o	72	7.6%
p	56	5.9%
c	54	5.7%
b	51	5.4%
e	50	5.3%
C	44	4.6%
r	30	3.2%
	28	3.0%
Other values (25)	201	21.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	947	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	278	29.4%
n	83	8.8%
o	72	7.6%
p	56	5.9%
c	54	5.7%
b	51	5.4%
e	50	5.3%
C	44	4.6%
r	30	3.2%
	28	3.0%
Other values (25)	201	21.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	947	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	278	29.4%
n	83	8.8%
o	72	7.6%
p	56	5.9%
c	54	5.7%
b	51	5.4%
e	50	5.3%
C	44	4.6%
r	30	3.2%
	28	3.0%
Other values (25)	201	21.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	947	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	278	29.4%
n	83	8.8%
o	72	7.6%
p	56	5.9%
c	54	5.7%
b	51	5.4%
e	50	5.3%
C	44	4.6%
r	30	3.2%
	28	3.0%
Other values (25)	201	21.2%

host_listings_count
Real number (ℝ)

Distinct	12
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.93

Minimum	1
Maximum	144
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	3
Q3	5
95-th percentile	10.1
Maximum	144
Range	143
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	14.372571
Coefficient of variation (CV)	2.9153289
Kurtosis	90.998365
Mean	4.93
Median Absolute Deviation (MAD)	2
Skewness	9.3431675
Sum	493
Variance	206.57081
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
1	33	33.0%
2	16	16.0%
4	11	11.0%
5	10	10.0%
3	9	9.0%
6	9	9.0%
7	4	4.0%
12	3	3.0%
8	2	2.0%
19	1	1.0%
Other values (2)	2	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	33	33.0%
2	16	16.0%
3	9	9.0%
4	11	11.0%
5	10	10.0%
6	9	9.0%
7	4	4.0%
8	2	2.0%
10	1	1.0%
12	3	3.0%

Value	Count	Frequency (%)
144	1	1.0%
19	1	1.0%
12	3	3.0%
10	1	1.0%
8	2	2.0%
7	4	4.0%
6	9	9.0%
5	10	10.0%
4	11	11.0%
3	9	9.0%

host_total_listings_count
Real number (ℝ)

Distinct	21
Distinct (%)	21.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.09

Minimum	1
Maximum	429
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2.75
median	5
Q3	8
95-th percentile	27.05
Maximum	429
Range	428
Interquartile range (IQR)	5.25

Descriptive statistics

Standard deviation	42.776869
Coefficient of variation (CV)	3.857247
Kurtosis	94.675462
Mean	11.09
Median Absolute Deviation (MAD)	3
Skewness	9.6114809
Sum	1109
Variance	1829.8605
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
3	13	13.0%
1	13	13.0%
2	12	12.0%
6	9	9.0%
4	8	8.0%
5	8	8.0%
8	8	8.0%
10	7	7.0%
7	6	6.0%
15	3	3.0%
Other values (11)	13	13.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	13	13.0%
2	12	12.0%
3	13	13.0%
4	8	8.0%
5	8	8.0%
6	9	9.0%
7	6	6.0%
8	8	8.0%
9	1	1.0%
10	7	7.0%

Value	Count	Frequency (%)
429	1	1.0%
33	2	2.0%
31	1	1.0%
28	1	1.0%
27	1	1.0%
23	1	1.0%
21	1	1.0%
17	1	1.0%
15	3	3.0%
13	1	1.0%

host_verifications
Categorical

IMBALANCE

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

['email', 'phone']	86
['email', 'phone', 'work_email']	10
['phone']	3
['email']	1

Length

Max length	32
Median length	18
Mean length	19.04
Min length	9

Characters and Unicode

Total characters	1904
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	['email', 'phone']
2nd row	['email', 'phone']
3rd row	['email', 'phone']
4th row	['email', 'phone']
5th row	['email', 'phone']

Common Values

Value	Count	Frequency (%)
['email', 'phone']	86	86.0%
['email', 'phone', 'work_email']	10	10.0%
['phone']	3	3.0%
['email']	1	1.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
phone	99	48.1%
email	97	47.1%
work_email	10	4.9%

Most occurring characters

Value	Count	Frequency (%)
'	412	21.6%
e	206	10.8%
o	109	5.7%
m	107	5.6%
a	107	5.6%
i	107	5.6%
l	107	5.6%
,	106	5.6%
	106	5.6%
[	100	5.3%
Other values (8)	437	23.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1904	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	412	21.6%
e	206	10.8%
o	109	5.7%
m	107	5.6%
a	107	5.6%
i	107	5.6%
l	107	5.6%
,	106	5.6%
	106	5.6%
[	100	5.3%
Other values (8)	437	23.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1904	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	412	21.6%
e	206	10.8%
o	109	5.7%
m	107	5.6%
a	107	5.6%
i	107	5.6%
l	107	5.6%
,	106	5.6%
	106	5.6%
[	100	5.3%
Other values (8)	437	23.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1904	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	412	21.6%
e	206	10.8%
o	109	5.7%
m	107	5.6%
a	107	5.6%
i	107	5.6%
l	107	5.6%
,	106	5.6%
	106	5.6%
[	100	5.3%
Other values (8)	437	23.0%

host_has_profile_pic
Boolean

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

True	100

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	100	100.0%

host_identity_verified
Boolean

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

True	83
False	17

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	83	83.0%
False	17	17.0%

neighbourhood
Categorical

IMBALANCE MISSING

Distinct	8
Distinct (%)	14.0%
Missing	43
Missing (%)	43.0%
Memory size	932.0 B

Rio de Janeiro, Brazil	46
Rio, Rio de Janeiro, Brazil	5
Ipanema, Rio de Janeiro, Brazil	1
Rio de Janeiro, Rj, Brazil	1
Joatinga, Rio de Janeiro, Brazil	1
Other values (3)	3

Length

Max length	39
Median length	22
Mean length	23.684211
Min length	22

Characters and Unicode

Total characters	1350
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	10.5%

Sample

1st row	Rio de Janeiro, Brazil
2nd row	Rio de Janeiro, Brazil
3rd row	Rio de Janeiro, Brazil
4th row	Rio de Janeiro, Brazil
5th row	Ipanema, Rio de Janeiro, Brazil

Common Values

Value	Count	Frequency (%)
Rio de Janeiro, Brazil	46	46.0%
Rio, Rio de Janeiro, Brazil	5	5.0%
Ipanema, Rio de Janeiro, Brazil	1	1.0%
Rio de Janeiro, Rj, Brazil	1	1.0%
Joatinga, Rio de Janeiro, Brazil	1	1.0%
Santa Teresa, Rio de Janeiro, Brazil	1	1.0%
Rio de Janeiro , Rio de Janeiro, Brazil	1	1.0%
Rio de janeiro , Rio de Janeiro, Brazil	1	1.0%
(Missing)	43	43.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
rio	64	26.0%
de	59	24.0%
janeiro	59	24.0%
brazil	57	23.2%
	2	0.8%
ipanema	1	0.4%
rj	1	0.4%
joatinga	1	0.4%
santa	1	0.4%
teresa	1	0.4%

Most occurring characters

Value	Count	Frequency (%)
	189	14.0%
i	181	13.4%
o	124	9.2%
a	123	9.1%
e	121	9.0%
r	117	8.7%
,	68	5.0%
R	65	4.8%
n	62	4.6%
d	59	4.4%
Other values (13)	241	17.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1350	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	189	14.0%
i	181	13.4%
o	124	9.2%
a	123	9.1%
e	121	9.0%
r	117	8.7%
,	68	5.0%
R	65	4.8%
n	62	4.6%
d	59	4.4%
Other values (13)	241	17.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1350	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	189	14.0%
i	181	13.4%
o	124	9.2%
a	123	9.1%
e	121	9.0%
r	117	8.7%
,	68	5.0%
R	65	4.8%
n	62	4.6%
d	59	4.4%
Other values (13)	241	17.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1350	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	189	14.0%
i	181	13.4%
o	124	9.2%
a	123	9.1%
e	121	9.0%
r	117	8.7%
,	68	5.0%
R	65	4.8%
n	62	4.6%
d	59	4.4%
Other values (13)	241	17.9%

neighbourhood_cleansed
Categorical

Distinct	19
Distinct (%)	19.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Copacabana	43
Santa Teresa	11
Ipanema	10
Barra da Tijuca	6
Leblon	6
Other values (14)	24

Length

Max length	24
Median length	15
Mean length	9.71
Min length	3

Characters and Unicode

Total characters	971
Distinct characters	35
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7 ?
Unique (%)	7.0%

Sample

1st row	Copacabana
2nd row	Copacabana
3rd row	Copacabana
4th row	Copacabana
5th row	Copacabana

Common Values

Value	Count	Frequency (%)
Copacabana	43	43.0%
Santa Teresa	11	11.0%
Ipanema	10	10.0%
Barra da Tijuca	6	6.0%
Leblon	6	6.0%
Flamengo	4	4.0%
Botafogo	3	3.0%
Centro	2	2.0%
Leme	2	2.0%
Jardim Botânico	2	2.0%
Other values (9)	11	11.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
copacabana	43	33.3%
teresa	11	8.5%
santa	11	8.5%
ipanema	10	7.8%
da	7	5.4%
tijuca	7	5.4%
barra	6	4.7%
leblon	6	4.7%
flamengo	4	3.1%
botafogo	3	2.3%
Other values (15)	21	16.3%

Most occurring characters

Value	Count	Frequency (%)
a	280	28.8%
n	83	8.5%
o	72	7.4%
e	58	6.0%
p	55	5.7%
c	55	5.7%
b	49	5.0%
C	45	4.6%
r	35	3.6%
	29	3.0%
Other values (25)	210	21.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	971	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	280	28.8%
n	83	8.5%
o	72	7.4%
e	58	6.0%
p	55	5.7%
c	55	5.7%
b	49	5.0%
C	45	4.6%
r	35	3.6%
	29	3.0%
Other values (25)	210	21.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	971	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	280	28.8%
n	83	8.5%
o	72	7.4%
e	58	6.0%
p	55	5.7%
c	55	5.7%
b	49	5.0%
C	45	4.6%
r	35	3.6%
	29	3.0%
Other values (25)	210	21.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	971	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	280	28.8%
n	83	8.5%
o	72	7.4%
e	58	6.0%
p	55	5.7%
c	55	5.7%
b	49	5.0%
C	45	4.6%
r	35	3.6%
	29	3.0%
Other values (25)	210	21.6%

neighbourhood_group_cleansed
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

latitude
Real number (ℝ)

Distinct	99
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-22.967036

Minimum	-23.03154
Maximum	-22.84208
Zeros	0
Zeros (%)	0.0%
Negative	100
Negative (%)	100.0%
Memory size	932.0 B

Quantile statistics

Minimum	-23.03154
5-th percentile	-23.008247
Q1	-22.982385
median	-22.975741
Q3	-22.96198
95-th percentile	-22.917173
Maximum	-22.84208
Range	0.18946
Interquartile range (IQR)	0.020405

Descriptive statistics

Standard deviation	0.02841149
Coefficient of variation (CV)	-0.0012370552
Kurtosis	2.9387793
Mean	-22.967036
Median Absolute Deviation (MAD)	0.00964
Skewness	1.1718422
Sum	-2296.7036
Variance	0.00080721275
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-22.98127	2	2.0%
-22.96599	1	1.0%
-22.97369	1	1.0%
-22.95508	1	1.0%
-23.01469	1	1.0%
-22.9754828	1	1.0%
-23.01524	1	1.0%
-22.96689	1	1.0%
-22.96102	1	1.0%
-22.91742	1	1.0%
Other values (89)	89	89.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-23.03154	1	1.0%
-23.01524	1	1.0%
-23.01469	1	1.0%
-23.01147	1	1.0%
-23.01124	1	1.0%
-23.00809	1	1.0%
-23.00451	1	1.0%
-23.00291	1	1.0%
-22.99508	1	1.0%
-22.98812	1	1.0%

Value	Count	Frequency (%)
-22.84208	1	1.0%
-22.9114	1	1.0%
-22.91258	1	1.0%
-22.91491	1	1.0%
-22.91666	1	1.0%
-22.9172	1	1.0%
-22.91742	1	1.0%
-22.91825	1	1.0%
-22.92099	1	1.0%
-22.92129	1	1.0%

longitude
Real number (ℝ)

Distinct	97
Distinct (%)	97.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-43.210403

Minimum	-43.47437
Maximum	-43.16858
Zeros	0
Zeros (%)	0.0%
Negative	100
Negative (%)	100.0%
Memory size	932.0 B

Quantile statistics

Minimum	-43.47437
5-th percentile	-43.364283
Q1	-43.203433
median	-43.19081
Q3	-43.182848
95-th percentile	-43.174956
Maximum	-43.16858
Range	0.30579
Interquartile range (IQR)	0.020585

Descriptive statistics

Standard deviation	0.055712981
Coefficient of variation (CV)	-0.0012893419
Kurtosis	7.4560728
Mean	-43.210403
Median Absolute Deviation (MAD)	0.0086505
Skewness	-2.7289612
Sum	-4321.0403
Variance	0.0031039363
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-43.19215	2	2.0%
-43.18902	2	2.0%
-43.18969	2	2.0%
-43.1794	1	1.0%
-43.1901	1	1.0%
-43.19214	1	1.0%
-43.18251	1	1.0%
-43.3008	1	1.0%
-43.188548	1	1.0%
-43.30342	1	1.0%
Other values (87)	87	87.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-43.47437	1	1.0%
-43.39086	1	1.0%
-43.388355	1	1.0%
-43.38321	1	1.0%
-43.37081	1	1.0%
-43.36394	1	1.0%
-43.31572	1	1.0%
-43.30873	1	1.0%
-43.30342	1	1.0%
-43.3008	1	1.0%

Value	Count	Frequency (%)
-43.16858	1	1.0%
-43.17263	1	1.0%
-43.17389	1	1.0%
-43.17478	1	1.0%
-43.17488	1	1.0%
-43.17496	1	1.0%
-43.17514	1	1.0%
-43.17526	1	1.0%
-43.17563	1	1.0%
-43.17583	1	1.0%

property_type
Categorical

Distinct	11
Distinct (%)	11.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Entire rental unit	56
Private room in rental unit	16
Entire condo	10
Private room in home	7
Entire loft	4
Other values (6)	7

Length

Max length	33
Median length	18
Mean length	18.95
Min length	11

Characters and Unicode

Total characters	1895
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	5.0%

Sample

1st row	Entire condo
2nd row	Entire rental unit
3rd row	Entire loft
4th row	Entire rental unit
5th row	Entire condo

Common Values

Value	Count	Frequency (%)
Entire rental unit	56	56.0%
Private room in rental unit	16	16.0%
Entire condo	10	10.0%
Private room in home	7	7.0%
Entire loft	4	4.0%
Entire home	2	2.0%
Private room in townhouse	1	1.0%
Private room in bed and breakfast	1	1.0%
Entire guest suite	1	1.0%
Private room in guesthouse	1	1.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
entire	73	22.1%
rental	72	21.8%
unit	72	21.8%
private	27	8.2%
room	27	8.2%
in	27	8.2%
condo	10	3.0%
home	9	2.7%
loft	4	1.2%
guest	2	0.6%
Other values (6)	7	2.1%

Most occurring characters

Value	Count	Frequency (%)
n	256	13.5%
t	255	13.5%
	230	12.1%
i	201	10.6%
r	200	10.6%
e	190	10.0%
a	102	5.4%
o	90	4.7%
u	79	4.2%
l	76	4.0%
Other values (13)	216	11.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1895	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	256	13.5%
t	255	13.5%
	230	12.1%
i	201	10.6%
r	200	10.6%
e	190	10.0%
a	102	5.4%
o	90	4.7%
u	79	4.2%
l	76	4.0%
Other values (13)	216	11.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1895	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	256	13.5%
t	255	13.5%
	230	12.1%
i	201	10.6%
r	200	10.6%
e	190	10.0%
a	102	5.4%
o	90	4.7%
u	79	4.2%
l	76	4.0%
Other values (13)	216	11.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1895	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	256	13.5%
t	255	13.5%
	230	12.1%
i	201	10.6%
r	200	10.6%
e	190	10.0%
a	102	5.4%
o	90	4.7%
u	79	4.2%
l	76	4.0%
Other values (13)	216	11.4%

room_type
Categorical

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

Entire home/apt	73
Private room	27

Length

Max length	15
Median length	15
Mean length	14.19
Min length	12

Characters and Unicode

Total characters	1419
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Entire home/apt
2nd row	Entire home/apt
3rd row	Entire home/apt
4th row	Entire home/apt
5th row	Entire home/apt

Common Values

Value	Count	Frequency (%)
Entire home/apt	73	73.0%
Private room	27	27.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
entire	73	36.5%
home/apt	73	36.5%
private	27	13.5%
room	27	13.5%

Most occurring characters

Value	Count	Frequency (%)
t	173	12.2%
e	173	12.2%
r	127	8.9%
o	127	8.9%
i	100	7.0%
	100	7.0%
m	100	7.0%
a	100	7.0%
E	73	5.1%
n	73	5.1%
Other values (5)	273	19.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1419	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	173	12.2%
e	173	12.2%
r	127	8.9%
o	127	8.9%
i	100	7.0%
	100	7.0%
m	100	7.0%
a	100	7.0%
E	73	5.1%
n	73	5.1%
Other values (5)	273	19.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1419	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	173	12.2%
e	173	12.2%
r	127	8.9%
o	127	8.9%
i	100	7.0%
	100	7.0%
m	100	7.0%
a	100	7.0%
E	73	5.1%
n	73	5.1%
Other values (5)	273	19.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1419	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	173	12.2%
e	173	12.2%
r	127	8.9%
o	127	8.9%
i	100	7.0%
	100	7.0%
m	100	7.0%
a	100	7.0%
E	73	5.1%
n	73	5.1%
Other values (5)	273	19.2%

accommodates
Real number (ℝ)

Distinct	13
Distinct (%)	13.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.92

Minimum	1
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1.95
Q1	2
median	3
Q3	4.25
95-th percentile	9.05
Maximum	16
Range	15
Interquartile range (IQR)	2.25

Descriptive statistics

Standard deviation	2.6767989
Coefficient of variation (CV)	0.68285687
Kurtosis	6.572748
Mean	3.92
Median Absolute Deviation (MAD)	1
Skewness	2.3055731
Sum	392
Variance	7.1652525
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
2	31	31.0%
4	24	24.0%
3	15	15.0%
6	9	9.0%
5	8	8.0%
1	5	5.0%
8	2	2.0%
13	1	1.0%
9	1	1.0%
16	1	1.0%
Other values (3)	3	3.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	5	5.0%
2	31	31.0%
3	15	15.0%
4	24	24.0%
5	8	8.0%
6	9	9.0%
8	2	2.0%
9	1	1.0%
10	1	1.0%
12	1	1.0%

Value	Count	Frequency (%)
16	1	1.0%
14	1	1.0%
13	1	1.0%
12	1	1.0%
10	1	1.0%
9	1	1.0%
8	2	2.0%
6	9	9.0%
5	8	8.0%
4	24	24.0%

bathrooms
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

bathrooms_text
Categorical

Distinct	13
Distinct (%)	13.1%
Missing	1
Missing (%)	1.0%
Memory size	932.0 B

1 bath	50
2 baths	9
1.5 baths	8
1 shared bath	6
2.5 baths	6
Other values (8)	20

Length

Max length	16
Median length	6
Mean length	7.6767677
Min length	6

Characters and Unicode

Total characters	760
Distinct characters	19
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	3.0%

Sample

1st row	1 bath
2nd row	1 bath
3rd row	1.5 baths
4th row	1 bath
5th row	1 bath

Common Values

Value	Count	Frequency (%)
1 bath	50	50.0%
2 baths	9	9.0%
1.5 baths	8	8.0%
1 shared bath	6	6.0%
2.5 baths	6	6.0%
1 private bath	5	5.0%
3 baths	4	4.0%
7 baths	3	3.0%
5 baths	3	3.0%
4 baths	2	2.0%
Other values (3)	3	3.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1	61	28.9%
bath	61	28.9%
baths	38	18.0%
2	9	4.3%
1.5	8	3.8%
shared	8	3.8%
2.5	7	3.3%
private	5	2.4%
3	4	1.9%
5	4	1.9%
Other values (3)	6	2.8%

Most occurring characters

Value	Count	Frequency (%)
a	112	14.7%
	112	14.7%
h	107	14.1%
t	104	13.7%
b	99	13.0%
1	69	9.1%
s	46	6.1%
5	20	2.6%
.	16	2.1%
2	16	2.1%
Other values (9)	59	7.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	760	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	112	14.7%
	112	14.7%
h	107	14.1%
t	104	13.7%
b	99	13.0%
1	69	9.1%
s	46	6.1%
5	20	2.6%
.	16	2.1%
2	16	2.1%
Other values (9)	59	7.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	760	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	112	14.7%
	112	14.7%
h	107	14.1%
t	104	13.7%
b	99	13.0%
1	69	9.1%
s	46	6.1%
5	20	2.6%
.	16	2.1%
2	16	2.1%
Other values (9)	59	7.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	760	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	112	14.7%
	112	14.7%
h	107	14.1%
t	104	13.7%
b	99	13.0%
1	69	9.1%
s	46	6.1%
5	20	2.6%
.	16	2.1%
2	16	2.1%
Other values (9)	59	7.8%

bedrooms
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

beds
Real number (ℝ)

Distinct	10
Distinct (%)	10.1%
Missing	1
Missing (%)	1.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.6464646

Minimum	1
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	7
Maximum	16
Range	15
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.4172557
Coefficient of variation (CV)	0.91339051
Kurtosis	9.871837
Mean	2.6464646
Median Absolute Deviation (MAD)	1
Skewness	2.6947717
Sum	262
Variance	5.8431251
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	40	40.0%
2	24	24.0%
3	14	14.0%
4	8	8.0%
7	5	5.0%
5	3	3.0%
10	2	2.0%
16	1	1.0%
6	1	1.0%
8	1	1.0%
(Missing)	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	40	40.0%
2	24	24.0%
3	14	14.0%
4	8	8.0%
5	3	3.0%
6	1	1.0%
7	5	5.0%
8	1	1.0%
10	2	2.0%
16	1	1.0%

Value	Count	Frequency (%)
16	1	1.0%
10	2	2.0%
8	1	1.0%
7	5	5.0%
6	1	1.0%
5	3	3.0%
4	8	8.0%
3	14	14.0%
2	24	24.0%
1	40	40.0%

amenities
Categorical

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

[]	100

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	200
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Common Values

Value	Count	Frequency (%)
[]	100	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
[	100	50.0%
]	100	50.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	100	50.0%
]	100	50.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	100	50.0%
]	100	50.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	100	50.0%
]	100	50.0%

price
Text

MISSING

Distinct	89
Distinct (%)	90.8%
Missing	2
Missing (%)	2.0%
Memory size	932.0 B

Length

Max length	9
Median length	7
Mean length	7.5
Min length	6

Characters and Unicode

Total characters	735
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	83 ?
Unique (%)	84.7%

Sample

1st row	$1,357.00
2nd row	$865.00
3rd row	$373.00
4th row	$1,701.00
5th row	$366.00

Value	Count	Frequency (%)
500.00	5	5.1%
250.00	2	2.0%
734.00	2	2.0%
300.00	2	2.0%
437.00	2	2.0%
169.00	2	2.0%
409.00	1	1.0%
1,701.00	1	1.0%
366.00	1	1.0%
368.00	1	1.0%
Other values (79)	79	80.6%

Most occurring characters

Value	Count	Frequency (%)
0	249	33.9%
$	98	13.3%
.	98	13.3%
1	38	5.2%
3	37	5.0%
6	35	4.8%
4	30	4.1%
5	29	3.9%
7	29	3.9%
9	25	3.4%
Other values (3)	67	9.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	249	33.9%
$	98	13.3%
.	98	13.3%
1	38	5.2%
3	37	5.0%
6	35	4.8%
4	30	4.1%
5	29	3.9%
7	29	3.9%
9	25	3.4%
Other values (3)	67	9.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	249	33.9%
$	98	13.3%
.	98	13.3%
1	38	5.2%
3	37	5.0%
6	35	4.8%
4	30	4.1%
5	29	3.9%
7	29	3.9%
9	25	3.4%
Other values (3)	67	9.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	249	33.9%
$	98	13.3%
.	98	13.3%
1	38	5.2%
3	37	5.0%
6	35	4.8%
4	30	4.1%
5	29	3.9%
7	29	3.9%
9	25	3.4%
Other values (3)	67	9.1%

minimum_nights
Real number (ℝ)

Distinct	10
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.2

Minimum	1
Maximum	78
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	3
95-th percentile	6.7
Maximum	78
Range	77
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	8.8454748
Coefficient of variation (CV)	2.1060654
Kurtosis	50.753959
Mean	4.2
Median Absolute Deviation (MAD)	1
Skewness	6.6249504
Sum	420
Variance	78.242424
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
3	33	33.0%
2	25	25.0%
1	22	22.0%
5	7	7.0%
4	7	7.0%
30	2	2.0%
20	1	1.0%
6	1	1.0%
22	1	1.0%
78	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	22	22.0%
2	25	25.0%
3	33	33.0%
4	7	7.0%
5	7	7.0%
6	1	1.0%
20	1	1.0%
22	1	1.0%
30	2	2.0%
78	1	1.0%

Value	Count	Frequency (%)
78	1	1.0%
30	2	2.0%
22	1	1.0%
20	1	1.0%
6	1	1.0%
5	7	7.0%
4	7	7.0%
3	33	33.0%
2	25	25.0%
1	22	22.0%

maximum_nights
Real number (ℝ)

Distinct	25
Distinct (%)	25.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	295.59

Minimum	7
Maximum	1125
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	7
5-th percentile	13.8
Q1	30
median	90
Q3	365
95-th percentile	1125
Maximum	1125
Range	1118
Interquartile range (IQR)	335

Descriptive statistics

Standard deviation	395.61667
Coefficient of variation (CV)	1.3383967
Kurtosis	0.22806384
Mean	295.59
Median Absolute Deviation (MAD)	60
Skewness	1.3622367
Sum	29559
Variance	156512.55
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
90	21	21.0%
30	17	17.0%
1125	15	15.0%
89	8	8.0%
365	6	6.0%
180	4	4.0%
28	3	3.0%
60	3	3.0%
730	3	3.0%
7	2	2.0%
Other values (15)	18	18.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7	2	2.0%
9	1	1.0%
10	2	2.0%
14	2	2.0%
15	1	1.0%
20	1	1.0%
21	1	1.0%
28	3	3.0%
29	1	1.0%
30	17	17.0%

Value	Count	Frequency (%)
1125	15	15.0%
760	2	2.0%
750	1	1.0%
730	3	3.0%
520	1	1.0%
500	1	1.0%
420	1	1.0%
365	6	6.0%
180	4	4.0%
150	1	1.0%

minimum_minimum_nights
Real number (ℝ)

Distinct	10
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.98

Minimum	1
Maximum	78
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	6.7
Maximum	78
Range	77
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	8.896691
Coefficient of variation (CV)	2.2353495
Kurtosis	50.200504
Mean	3.98
Median Absolute Deviation (MAD)	1
Skewness	6.5821906
Sum	398
Variance	79.151111
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	32	32.0%
2	26	26.0%
3	24	24.0%
5	8	8.0%
4	4	4.0%
30	2	2.0%
20	1	1.0%
6	1	1.0%
22	1	1.0%
78	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	32	32.0%
2	26	26.0%
3	24	24.0%
4	4	4.0%
5	8	8.0%
6	1	1.0%
20	1	1.0%
22	1	1.0%
30	2	2.0%
78	1	1.0%

Value	Count	Frequency (%)
78	1	1.0%
30	2	2.0%
22	1	1.0%
20	1	1.0%
6	1	1.0%
5	8	8.0%
4	4	4.0%
3	24	24.0%
2	26	26.0%
1	32	32.0%

maximum_minimum_nights
Real number (ℝ)

Distinct	13
Distinct (%)	13.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.14

Minimum	1
Maximum	78
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	5
95-th percentile	10.5
Maximum	78
Range	77
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	8.8077331
Coefficient of variation (CV)	1.7135667
Kurtosis	48.770802
Mean	5.14
Median Absolute Deviation (MAD)	2
Skewness	6.3948795
Sum	514
Variance	77.576162
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
3	24	24.0%
5	21	21.0%
1	18	18.0%
2	13	13.0%
4	8	8.0%
7	5	5.0%
6	3	3.0%
9	2	2.0%
30	2	2.0%
20	1	1.0%
Other values (3)	3	3.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	18	18.0%
2	13	13.0%
3	24	24.0%
4	8	8.0%
5	21	21.0%
6	3	3.0%
7	5	5.0%
9	2	2.0%
10	1	1.0%
20	1	1.0%

Value	Count	Frequency (%)
78	1	1.0%
30	2	2.0%
22	1	1.0%
20	1	1.0%
10	1	1.0%
9	2	2.0%
7	5	5.0%
6	3	3.0%
5	21	21.0%
4	8	8.0%

minimum_maximum_nights
Real number (ℝ)

Distinct	22
Distinct (%)	22.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	474.58

Minimum	1
Maximum	1125
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	9.95
Q1	52.5
median	121
Q3	1125
95-th percentile	1125
Maximum	1125
Range	1124
Interquartile range (IQR)	1072.5

Descriptive statistics

Standard deviation	488.96006
Coefficient of variation (CV)	1.0303006
Kurtosis	-1.667577
Mean	474.58
Median Absolute Deviation (MAD)	113
Skewness	0.46483146
Sum	47458
Variance	239081.94
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
1125	33	33.0%
90	16	16.0%
30	13	13.0%
365	6	6.0%
89	5	5.0%
180	3	3.0%
60	3	3.0%
28	2	2.0%
730	2	2.0%
1	2	2.0%
Other values (12)	15	15.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	2.0%
7	2	2.0%
9	1	1.0%
10	2	2.0%
14	1	1.0%
20	1	1.0%
21	1	1.0%
28	2	2.0%
30	13	13.0%
60	3	3.0%

Value	Count	Frequency (%)
1125	33	33.0%
760	2	2.0%
750	1	1.0%
730	2	2.0%
520	1	1.0%
500	1	1.0%
365	6	6.0%
180	3	3.0%
150	1	1.0%
92	1	1.0%

maximum_maximum_nights
Real number (ℝ)

Distinct	22
Distinct (%)	22.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	508.09

Minimum	7
Maximum	1125
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	7
5-th percentile	14.95
Q1	81.75
median	180
Q3	1125
95-th percentile	1125
Maximum	1125
Range	1118
Interquartile range (IQR)	1043.25

Descriptive statistics

Standard deviation	494.13054
Coefficient of variation (CV)	0.97252562
Kurtosis	-1.7804919
Mean	508.09
Median Absolute Deviation (MAD)	172
Skewness	0.33908625
Sum	50809
Variance	244164.99
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
1125	36	36.0%
90	16	16.0%
30	12	12.0%
365	6	6.0%
89	5	5.0%
180	3	3.0%
60	3	3.0%
28	2	2.0%
730	2	2.0%
10	2	2.0%
Other values (12)	13	13.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7	1	1.0%
9	1	1.0%
10	2	2.0%
14	1	1.0%
15	1	1.0%
20	1	1.0%
21	1	1.0%
28	2	2.0%
30	12	12.0%
60	3	3.0%

Value	Count	Frequency (%)
1125	36	36.0%
760	2	2.0%
750	1	1.0%
730	2	2.0%
520	1	1.0%
500	1	1.0%
365	6	6.0%
180	3	3.0%
150	1	1.0%
92	1	1.0%

minimum_nights_avg_ntm
Real number (ℝ)

Distinct	25
Distinct (%)	25.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.357

Minimum	1
Maximum	78
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	3.225
95-th percentile	7.65
Maximum	78
Range	77
Interquartile range (IQR)	1.225

Descriptive statistics

Standard deviation	8.8295676
Coefficient of variation (CV)	2.0265246
Kurtosis	50.651176
Mean	4.357
Median Absolute Deviation (MAD)	1
Skewness	6.6083156
Sum	435.7
Variance	77.961264
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
3	22	22.0%
1	19	19.0%
2	13	13.0%
5	7	7.0%
4	7	7.0%
2.1	6	6.0%
3.1	3	3.0%
2.3	3	3.0%
2.7	2	2.0%
30	2	2.0%
Other values (15)	16	16.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	19	19.0%
1.3	1	1.0%
1.9	1	1.0%
2	13	13.0%
2.1	6	6.0%
2.2	1	1.0%
2.3	3	3.0%
2.7	2	2.0%
2.8	1	1.0%
2.9	1	1.0%

Value	Count	Frequency (%)
78	1	1.0%
30	2	2.0%
22	1	1.0%
20	1	1.0%
7	1	1.0%
6	1	1.0%
5.2	1	1.0%
5	7	7.0%
4.9	1	1.0%
4	7	7.0%

maximum_nights_avg_ntm
Real number (ℝ)

Distinct	25
Distinct (%)	25.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	494.424

Minimum	7
Maximum	1125
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	7
5-th percentile	14.665
Q1	81.75
median	180
Q3	1125
95-th percentile	1125
Maximum	1125
Range	1118
Interquartile range (IQR)	1043.25

Descriptive statistics

Standard deviation	488.38064
Coefficient of variation (CV)	0.98777696
Kurtosis	-1.7276972
Mean	494.424
Median Absolute Deviation (MAD)	170.5
Skewness	0.39060018
Sum	49442.4
Variance	238515.65
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
1125	33	33.0%
90	16	16.0%
30	12	12.0%
365	6	6.0%
89	5	5.0%
180	3	3.0%
60	3	3.0%
28	2	2.0%
730	2	2.0%
10	2	2.0%
Other values (15)	16	16.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7	1	1.0%
9	1	1.0%
10	2	2.0%
14	1	1.0%
14.7	1	1.0%
20	1	1.0%
21	1	1.0%
28	2	2.0%
30	12	12.0%
60	3	3.0%

Value	Count	Frequency (%)
1125	33	33.0%
1114.7	1	1.0%
782.7	1	1.0%
760	2	2.0%
750	1	1.0%
730	2	2.0%
520	1	1.0%
500	1	1.0%
365	6	6.0%
180	3	3.0%

calendar_updated
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

has_availability
Boolean

CONSTANT MISSING

Distinct	1
Distinct (%)	1.0%
Missing	2
Missing (%)	2.0%
Memory size	332.0 B

True	98
(Missing)	2

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	98	98.0%
(Missing)	2	2.0%

availability_30
Real number (ℝ)

ZEROS

Distinct	29
Distinct (%)	29.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.8

Minimum	0
Maximum	30
Zeros	25
Zeros (%)	25.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.75
median	5.5
Q3	19.25
95-th percentile	30
Maximum	30
Range	30
Interquartile range (IQR)	18.5

Descriptive statistics

Standard deviation	10.982999
Coefficient of variation (CV)	1.0169443
Kurtosis	-1.2039074
Mean	10.8
Median Absolute Deviation (MAD)	5.5
Skewness	0.5882097
Sum	1080
Variance	120.62626
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
0	25	25.0%
30	10	10.0%
3	7	7.0%
5	5	5.0%
2	5	5.0%
1	5	5.0%
19	4	4.0%
24	3	3.0%
18	3	3.0%
6	3	3.0%
Other values (19)	30	30.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	25	25.0%
1	5	5.0%
2	5	5.0%
3	7	7.0%
4	3	3.0%
5	5	5.0%
6	3	3.0%
7	1	1.0%
8	2	2.0%
9	1	1.0%

Value	Count	Frequency (%)
30	10	10.0%
29	2	2.0%
28	2	2.0%
27	1	1.0%
26	1	1.0%
25	1	1.0%
24	3	3.0%
23	1	1.0%
22	1	1.0%
21	2	2.0%

availability_60
Real number (ℝ)

ZEROS

Distinct	43
Distinct (%)	43.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.58

Minimum	0
Maximum	60
Zeros	20
Zeros (%)	20.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.75
median	19.5
Q3	39.25
95-th percentile	60
Maximum	60
Range	60
Interquartile range (IQR)	35.5

Descriptive statistics

Standard deviation	21.143655
Coefficient of variation (CV)	0.89667748
Kurtosis	-1.1841256
Mean	23.58
Median Absolute Deviation (MAD)	18.5
Skewness	0.47326156
Sum	2358
Variance	447.05414
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=43)

Value	Count	Frequency (%)
0	20	20.0%
60	8	8.0%
9	6	6.0%
38	4	4.0%
51	4	4.0%
7	3	3.0%
20	3	3.0%
19	3	3.0%
5	2	2.0%
2	2	2.0%
Other values (33)	45	45.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	20	20.0%
1	2	2.0%
2	2	2.0%
3	1	1.0%
4	1	1.0%
5	2	2.0%
6	2	2.0%
7	3	3.0%
9	6	6.0%
10	1	1.0%

Value	Count	Frequency (%)
60	8	8.0%
59	2	2.0%
58	2	2.0%
57	1	1.0%
54	2	2.0%
52	1	1.0%
51	4	4.0%
46	1	1.0%
45	1	1.0%
44	1	1.0%

availability_90
Real number (ℝ)

ZEROS

Distinct	55
Distinct (%)	55.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	41.13

Minimum	0
Maximum	90
Zeros	19
Zeros (%)	19.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	10
median	40
Q3	69
95-th percentile	90
Maximum	90
Range	90
Interquartile range (IQR)	59

Descriptive statistics

Standard deviation	32.111125
Coefficient of variation (CV)	0.78072271
Kurtosis	-1.3812719
Mean	41.13
Median Absolute Deviation (MAD)	29.5
Skewness	0.12127216
Sum	4113
Variance	1031.1243
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	19	19.0%
90	8	8.0%
81	4	4.0%
26	3	3.0%
88	2	2.0%
63	2	2.0%
49	2	2.0%
69	2	2.0%
34	2	2.0%
54	2	2.0%
Other values (45)	54	54.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	19	19.0%
1	1	1.0%
2	1	1.0%
3	1	1.0%
4	1	1.0%
6	1	1.0%
10	2	2.0%
11	1	1.0%
12	1	1.0%
13	2	2.0%

Value	Count	Frequency (%)
90	8	8.0%
89	2	2.0%
88	2	2.0%
87	1	1.0%
84	2	2.0%
82	1	1.0%
81	4	4.0%
76	1	1.0%
74	1	1.0%
73	1	1.0%

availability_365
Real number (ℝ)

ZEROS

Distinct	73
Distinct (%)	73.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	189.47

Minimum	0
Maximum	365
Zeros	12
Zeros (%)	12.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	40
median	230.5
Q3	319
95-th percentile	365
Maximum	365
Range	365
Interquartile range (IQR)	279

Descriptive statistics

Standard deviation	137.36153
Coefficient of variation (CV)	0.72497775
Kurtosis	-1.5853573
Mean	189.47
Median Absolute Deviation (MAD)	126
Skewness	-0.17502219
Sum	18947
Variance	18868.191
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	12	12.0%
365	8	8.0%
319	3	3.0%
269	2	2.0%
356	2	2.0%
31	2	2.0%
264	2	2.0%
363	2	2.0%
171	2	2.0%
44	2	2.0%
Other values (63)	63	63.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	12	12.0%
1	1	1.0%
2	1	1.0%
3	1	1.0%
10	1	1.0%
16	1	1.0%
18	1	1.0%
20	1	1.0%
26	1	1.0%
30	1	1.0%

Value	Count	Frequency (%)
365	8	8.0%
364	1	1.0%
363	2	2.0%
362	1	1.0%
357	1	1.0%
356	2	2.0%
351	1	1.0%
345	1	1.0%
339	1	1.0%
338	1	1.0%

calendar_last_scraped
Categorical

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

2023-12-27	40
2023-12-26	34
2023-12-28	17
2023-12-30	8
2023-12-29	1

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	1000
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2023-12-27
2nd row	2023-12-27
3rd row	2023-12-27
4th row	2023-12-27
5th row	2023-12-27

Common Values

Value	Count	Frequency (%)
2023-12-27	40	40.0%
2023-12-26	34	34.0%
2023-12-28	17	17.0%
2023-12-30	8	8.0%
2023-12-29	1	1.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2023-12-27	40	40.0%
2023-12-26	34	34.0%
2023-12-28	17	17.0%
2023-12-30	8	8.0%
2023-12-29	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	392	39.2%
-	200	20.0%
0	108	10.8%
3	108	10.8%
1	100	10.0%
7	40	4.0%
6	34	3.4%
8	17	1.7%
9	1	0.1%

number_of_reviews
Real number (ℝ)

ZEROS

Distinct	77
Distinct (%)	77.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	112.38

Minimum	0
Maximum	555
Zeros	10
Zeros (%)	10.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	16.75
median	76
Q3	160.25
95-th percentile	353.65
Maximum	555
Range	555
Interquartile range (IQR)	143.5

Descriptive statistics

Standard deviation	121.17662
Coefficient of variation (CV)	1.0782757
Kurtosis	1.9164457
Mean	112.38
Median Absolute Deviation (MAD)	71.5
Skewness	1.4457571
Sum	11238
Variance	14683.773
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	10	10.0%
24	4	4.0%
12	3	3.0%
4	3	3.0%
37	2	2.0%
29	2	2.0%
7	2	2.0%
74	2	2.0%
2	2	2.0%
17	2	2.0%
Other values (67)	68	68.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	10	10.0%
1	1	1.0%
2	2	2.0%
3	1	1.0%
4	3	3.0%
5	1	1.0%
7	2	2.0%
11	1	1.0%
12	3	3.0%
16	1	1.0%

Value	Count	Frequency (%)
555	1	1.0%
463	1	1.0%
454	1	1.0%
431	1	1.0%
404	1	1.0%
351	1	1.0%
313	1	1.0%
311	1	1.0%
293	1	1.0%
281	1	1.0%

number_of_reviews_ltm
Real number (ℝ)

ZEROS

Distinct	34
Distinct (%)	34.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.7

Minimum	0
Maximum	65
Zeros	31
Zeros (%)	31.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	8
Q3	25.25
95-th percentile	36
Maximum	65
Range	65
Interquartile range (IQR)	25.25

Descriptive statistics

Standard deviation	15.25507
Coefficient of variation (CV)	1.1135088
Kurtosis	1.1552853
Mean	13.7
Median Absolute Deviation (MAD)	8
Skewness	1.1728045
Sum	1370
Variance	232.71717
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
0	31	31.0%
3	5	5.0%
29	4	4.0%
4	4	4.0%
6	4	4.0%
22	4	4.0%
36	4	4.0%
31	4	4.0%
27	3	3.0%
13	3	3.0%
Other values (24)	34	34.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	31	31.0%
1	2	2.0%
2	1	1.0%
3	5	5.0%
4	4	4.0%
5	1	1.0%
6	4	4.0%
7	1	1.0%
8	3	3.0%
10	3	3.0%

Value	Count	Frequency (%)
65	1	1.0%
64	1	1.0%
54	1	1.0%
51	1	1.0%
36	4	4.0%
34	1	1.0%
33	1	1.0%
31	4	4.0%
30	2	2.0%
29	4	4.0%

number_of_reviews_l30d
Real number (ℝ)

ZEROS

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.74

Minimum	0
Maximum	6
Zeros	64
Zeros (%)	64.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	3
Maximum	6
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.1859446
Coefficient of variation (CV)	1.6026279
Kurtosis	3.4443115
Mean	0.74
Median Absolute Deviation (MAD)	0
Skewness	1.7819181
Sum	74
Variance	1.4064646
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	64	64.0%
2	15	15.0%
1	12	12.0%
3	6	6.0%
4	2	2.0%
6	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	64	64.0%
1	12	12.0%
2	15	15.0%
3	6	6.0%
4	2	2.0%
6	1	1.0%

Value	Count	Frequency (%)
6	1	1.0%
4	2	2.0%
3	6	6.0%
2	15	15.0%
1	12	12.0%
0	64	64.0%

first_review
Date

MISSING

Distinct	81
Distinct (%)	90.0%
Missing	10
Missing (%)	10.0%
Memory size	932.0 B

Minimum	2010-06-07 00:00:00
Maximum	2021-08-12 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

last_review
Date

MISSING

Distinct	61
Distinct (%)	67.8%
Missing	10
Missing (%)	10.0%
Memory size	932.0 B

Minimum	2012-02-21 00:00:00
Maximum	2023-12-25 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

review_scores_rating
Real number (ℝ)

MISSING

Distinct	46
Distinct (%)	51.1%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.7532222

Minimum	4
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	4
5-th percentile	4.268
Q1	4.685
median	4.8
Q3	4.88
95-th percentile	5
Maximum	5
Range	1
Interquartile range (IQR)	0.195

Descriptive statistics

Standard deviation	0.20825561
Coefficient of variation (CV)	0.043813565
Kurtosis	2.4589278
Mean	4.7532222
Median Absolute Deviation (MAD)	0.095
Skewness	-1.5093246
Sum	427.79
Variance	0.0433704
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
5	9	9.0%
4.78	5	5.0%
4.76	5	5.0%
4.8	4	4.0%
4.86	4	4.0%
4.92	4	4.0%
4.81	4	4.0%
4.82	3	3.0%
4.79	3	3.0%
4.87	3	3.0%
Other values (36)	46	46.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4	1	1.0%
4.14	1	1.0%
4.19	1	1.0%
4.21	1	1.0%
4.25	1	1.0%
4.29	1	1.0%
4.34	1	1.0%
4.4	1	1.0%
4.5	1	1.0%
4.51	1	1.0%

Value	Count	Frequency (%)
5	9	9.0%
4.98	2	2.0%
4.96	1	1.0%
4.95	1	1.0%
4.92	4	4.0%
4.91	1	1.0%
4.9	2	2.0%
4.89	2	2.0%
4.88	2	2.0%
4.87	3	3.0%

review_scores_accuracy
Real number (ℝ)

MISSING

Distinct	40
Distinct (%)	44.4%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.7697778

Minimum	3.88
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	3.88
5-th percentile	4.25
Q1	4.7225
median	4.83
Q3	4.9075
95-th percentile	5
Maximum	5
Range	1.12
Interquartile range (IQR)	0.185

Descriptive statistics

Standard deviation	0.22836487
Coefficient of variation (CV)	0.047877464
Kurtosis	5.0206713
Mean	4.7697778
Median Absolute Deviation (MAD)	0.095
Skewness	-2.13647
Sum	429.28
Variance	0.052150512
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
5	9	9.0%
4.83	7	7.0%
4.87	6	6.0%
4.86	5	5.0%
4.75	4	4.0%
4.93	4	4.0%
4.7	4	4.0%
4.73	4	4.0%
4.92	3	3.0%
4.72	3	3.0%
Other values (30)	41	41.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3.88	1	1.0%
3.92	1	1.0%
4	1	1.0%
4.24	1	1.0%
4.25	2	2.0%
4.33	1	1.0%
4.39	1	1.0%
4.43	1	1.0%
4.57	1	1.0%
4.58	1	1.0%

Value	Count	Frequency (%)
5	9	9.0%
4.98	1	1.0%
4.95	3	3.0%
4.94	1	1.0%
4.93	4	4.0%
4.92	3	3.0%
4.91	2	2.0%
4.9	2	2.0%
4.89	1	1.0%
4.88	1	1.0%

review_scores_cleanliness
Real number (ℝ)

MISSING

Distinct	50
Distinct (%)	55.6%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.7

Minimum	3.67
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	3.67
5-th percentile	4.206
Q1	4.595
median	4.765
Q3	4.8875
95-th percentile	5
Maximum	5
Range	1.33
Interquartile range (IQR)	0.2925

Descriptive statistics

Standard deviation	0.25547048
Coefficient of variation (CV)	0.054355422
Kurtosis	2.3296178
Mean	4.7
Median Absolute Deviation (MAD)	0.135
Skewness	-1.383327
Sum	423
Variance	0.065265169
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5	6	6.0%
4.93	5	5.0%
4.79	5	5.0%
4.74	4	4.0%
4.9	3	3.0%
4.67	3	3.0%
4.96	3	3.0%
4.71	3	3.0%
4.86	3	3.0%
4.88	3	3.0%
Other values (40)	52	52.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3.67	1	1.0%
4.01	1	1.0%
4.13	1	1.0%
4.15	1	1.0%
4.17	1	1.0%
4.25	2	2.0%
4.31	1	1.0%
4.33	2	2.0%
4.36	1	1.0%
4.4	2	2.0%

Value	Count	Frequency (%)
5	6	6.0%
4.99	1	1.0%
4.96	3	3.0%
4.95	1	1.0%
4.94	1	1.0%
4.93	5	5.0%
4.92	1	1.0%
4.9	3	3.0%
4.89	2	2.0%
4.88	3	3.0%

review_scores_checkin
Real number (ℝ)

MISSING

Distinct	29
Distinct (%)	32.2%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.8835556

Minimum	4.25
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	4.25
5-th percentile	4.7145
Q1	4.84
median	4.91
Q3	4.96
95-th percentile	5
Maximum	5
Range	0.75
Interquartile range (IQR)	0.12

Descriptive statistics

Standard deviation	0.12123254
Coefficient of variation (CV)	0.024824646
Kurtosis	11.654055
Mean	4.8835556
Median Absolute Deviation (MAD)	0.06
Skewness	-2.8143737
Sum	439.52
Variance	0.014697328
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
5	12	12.0%
4.97	8	8.0%
4.91	7	7.0%
4.96	7	7.0%
4.9	6	6.0%
4.83	5	5.0%
4.88	4	4.0%
4.89	4	4.0%
4.86	3	3.0%
4.8	3	3.0%
Other values (19)	31	31.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.25	1	1.0%
4.33	1	1.0%
4.67	1	1.0%
4.69	1	1.0%
4.71	1	1.0%
4.72	1	1.0%
4.73	2	2.0%
4.75	1	1.0%
4.78	2	2.0%
4.79	1	1.0%

Value	Count	Frequency (%)
5	12	12.0%
4.99	1	1.0%
4.97	8	8.0%
4.96	7	7.0%
4.95	3	3.0%
4.94	2	2.0%
4.93	3	3.0%
4.92	3	3.0%
4.91	7	7.0%
4.9	6	6.0%

review_scores_communication
Real number (ℝ)

MISSING

Distinct	32
Distinct (%)	35.6%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.883

Minimum	4.52
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	4.52
5-th percentile	4.648
Q1	4.83
median	4.91
Q3	4.96
95-th percentile	5
Maximum	5
Range	0.48
Interquartile range (IQR)	0.13

Descriptive statistics

Standard deviation	0.11125888
Coefficient of variation (CV)	0.022784945
Kurtosis	1.5949836
Mean	4.883
Median Absolute Deviation (MAD)	0.06
Skewness	-1.3504718
Sum	439.47
Variance	0.012378539
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
5	12	12.0%
4.96	7	7.0%
4.88	6	6.0%
4.93	5	5.0%
4.95	5	5.0%
4.97	5	5.0%
4.89	4	4.0%
4.83	4	4.0%
4.98	4	4.0%
4.87	4	4.0%
Other values (22)	34	34.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.52	1	1.0%
4.56	1	1.0%
4.57	1	1.0%
4.58	1	1.0%
4.63	1	1.0%
4.67	1	1.0%
4.7	1	1.0%
4.73	1	1.0%
4.74	2	2.0%
4.75	2	2.0%

Value	Count	Frequency (%)
5	12	12.0%
4.99	1	1.0%
4.98	4	4.0%
4.97	5	5.0%
4.96	7	7.0%
4.95	5	5.0%
4.94	2	2.0%
4.93	5	5.0%
4.92	3	3.0%
4.91	3	3.0%

review_scores_location
Real number (ℝ)

MISSING

Distinct	38
Distinct (%)	42.2%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.8276667

Minimum	4.25
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	4.25
5-th percentile	4.4345
Q1	4.75
median	4.89
Q3	4.94
95-th percentile	5
Maximum	5
Range	0.75
Interquartile range (IQR)	0.19

Descriptive statistics

Standard deviation	0.17017539
Coefficient of variation (CV)	0.035250029
Kurtosis	2.2552069
Mean	4.8276667
Median Absolute Deviation (MAD)	0.07
Skewness	-1.5884492
Sum	434.49
Variance	0.028959663
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
5	7	7.0%
4.93	7	7.0%
4.96	5	5.0%
4.91	5	5.0%
4.89	5	5.0%
4.75	5	5.0%
4.92	4	4.0%
4.95	4	4.0%
4.76	3	3.0%
4.94	3	3.0%
Other values (28)	42	42.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.25	1	1.0%
4.31	1	1.0%
4.33	1	1.0%
4.37	1	1.0%
4.43	1	1.0%
4.44	1	1.0%
4.53	1	1.0%
4.57	1	1.0%
4.58	2	2.0%
4.62	1	1.0%

Value	Count	Frequency (%)
5	7	7.0%
4.99	1	1.0%
4.98	2	2.0%
4.97	3	3.0%
4.96	5	5.0%
4.95	4	4.0%
4.94	3	3.0%
4.93	7	7.0%
4.92	4	4.0%
4.91	5	5.0%

review_scores_value
Real number (ℝ)

MISSING

Distinct	47
Distinct (%)	52.2%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.6606667

Minimum	4
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	4
5-th percentile	4.23
Q1	4.5625
median	4.705
Q3	4.78
95-th percentile	4.923
Maximum	5
Range	1
Interquartile range (IQR)	0.2175

Descriptive statistics

Standard deviation	0.19892859
Coefficient of variation (CV)	0.042682433
Kurtosis	1.4396919
Mean	4.6606667
Median Absolute Deviation (MAD)	0.085
Skewness	-1.0786436
Sum	419.46
Variance	0.039572584
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
4.67	6	6.0%
4.78	6	6.0%
4.75	6	6.0%
4.77	4	4.0%
4.79	4	4.0%
4.63	3	3.0%
4.73	3	3.0%
4.5	3	3.0%
5	3	3.0%
4.56	2	2.0%
Other values (37)	50	50.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4	1	1.0%
4.08	1	1.0%
4.19	1	1.0%
4.2	1	1.0%
4.23	2	2.0%
4.29	1	1.0%
4.33	1	1.0%
4.38	1	1.0%
4.43	1	1.0%
4.44	1	1.0%

Value	Count	Frequency (%)
5	3	3.0%
4.97	1	1.0%
4.95	1	1.0%
4.89	2	2.0%
4.88	1	1.0%
4.86	2	2.0%
4.85	1	1.0%
4.84	1	1.0%
4.83	2	2.0%
4.82	1	1.0%

license
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	100
Missing (%)	100.0%
Memory size	932.0 B

instant_bookable
Boolean

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	80
True	20

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	80	80.0%
True	20	20.0%

calculated_host_listings_count
Real number (ℝ)

Distinct	11
Distinct (%)	11.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.38

Minimum	1
Maximum	142
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	8.1
Maximum	142
Range	141
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	14.151975
Coefficient of variation (CV)	3.2310444
Kurtosis	92.890901
Mean	4.38
Median Absolute Deviation (MAD)	1
Skewness	9.4835238
Sum	438
Variance	200.27838
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
1	38	38.0%
2	18	18.0%
3	13	13.0%
5	9	9.0%
4	8	8.0%
6	6	6.0%
10	3	3.0%
7	2	2.0%
18	1	1.0%
8	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	38	38.0%
2	18	18.0%
3	13	13.0%
4	8	8.0%
5	9	9.0%
6	6	6.0%
7	2	2.0%
8	1	1.0%
10	3	3.0%
18	1	1.0%

Value	Count	Frequency (%)
142	1	1.0%
18	1	1.0%
10	3	3.0%
8	1	1.0%
7	2	2.0%
6	6	6.0%
5	9	9.0%
4	8	8.0%
3	13	13.0%
2	18	18.0%

calculated_host_listings_count_entire_homes
Real number (ℝ)

ZEROS

Distinct	13
Distinct (%)	13.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.72

Minimum	0
Maximum	142
Zeros	18
Zeros (%)	18.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	3
95-th percentile	8.05
Maximum	142
Range	142
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	14.233323
Coefficient of variation (CV)	3.826162
Kurtosis	92.529654
Mean	3.72
Median Absolute Deviation (MAD)	1
Skewness	9.4582809
Sum	372
Variance	202.58747
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
1	38	38.0%
0	18	18.0%
3	13	13.0%
2	10	10.0%
5	5	5.0%
6	4	4.0%
4	4	4.0%
9	2	2.0%
7	2	2.0%
18	1	1.0%
Other values (3)	3	3.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	18	18.0%
1	38	38.0%
2	10	10.0%
3	13	13.0%
4	4	4.0%
5	5	5.0%
6	4	4.0%
7	2	2.0%
8	1	1.0%
9	2	2.0%

Value	Count	Frequency (%)
142	1	1.0%
18	1	1.0%
10	1	1.0%
9	2	2.0%
8	1	1.0%
7	2	2.0%
6	4	4.0%
5	5	5.0%
4	4	4.0%
3	13	13.0%

calculated_host_listings_count_private_rooms
Real number (ℝ)

ZEROS

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.66

Minimum	0
Maximum	5
Zeros	68
Zeros (%)	68.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	3.05
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.240886
Coefficient of variation (CV)	1.8801303
Kurtosis	4.5982163
Mean	0.66
Median Absolute Deviation (MAD)	0
Skewness	2.2301484
Sum	66
Variance	1.539798
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	68	68.0%
1	16	16.0%
2	7	7.0%
3	4	4.0%
5	4	4.0%
4	1	1.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	68	68.0%
1	16	16.0%
2	7	7.0%
3	4	4.0%
4	1	1.0%
5	4	4.0%

Value	Count	Frequency (%)
5	4	4.0%
4	1	1.0%
3	4	4.0%
2	7	7.0%
1	16	16.0%
0	68	68.0%

calculated_host_listings_count_shared_rooms
Categorical

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

0	100

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	100
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	100	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	100	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	100	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	100	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	100	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	100	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	100	100.0%

reviews_per_month
Real number (ℝ)

MISSING

Distinct	73
Distinct (%)	81.1%
Missing	10
Missing (%)	10.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.89744444

Minimum	0.01
Maximum	3.8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	932.0 B

Quantile statistics

Minimum	0.01
5-th percentile	0.0345
Q1	0.2225
median	0.62
Q3	1.265
95-th percentile	2.649
Maximum	3.8
Range	3.79
Interquartile range (IQR)	1.0425

Descriptive statistics

Standard deviation	0.83117699
Coefficient of variation (CV)	0.92615983
Kurtosis	1.2703519
Mean	0.89744444
Median Absolute Deviation (MAD)	0.485
Skewness	1.2181412
Sum	80.77
Variance	0.69085519
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.28	2	2.0%
1.88	2	2.0%
0.02	2	2.0%
0.57	2	2.0%
0.25	2	2.0%
0.33	2	2.0%
0.56	2	2.0%
0.12	2	2.0%
0.07	2	2.0%
0.04	2	2.0%
Other values (63)	70	70.0%
(Missing)	10	10.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01	2	2.0%
0.02	2	2.0%
0.03	1	1.0%
0.04	2	2.0%
0.05	2	2.0%
0.07	2	2.0%
0.08	1	1.0%
0.09	1	1.0%
0.11	1	1.0%
0.12	2	2.0%

Value	Count	Frequency (%)
3.8	1	1.0%
3.11	1	1.0%
3.07	1	1.0%
2.82	2	2.0%
2.44	1	1.0%
2.13	1	1.0%
2.07	1	1.0%
1.96	1	1.0%
1.9	1	1.0%
1.88	2	2.0%

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	id	listing_url	scrape_id	last_scraped	source	name	description	neighborhood_overview	picture_url	host_id	host_url	host_name	host_since	host_location	host_about	host_response_time	host_response_rate	host_acceptance_rate	host_is_superhost	host_thumbnail_url	host_picture_url	host_neighbourhood	host_listings_count	host_total_listings_count	host_verifications	host_has_profile_pic	host_identity_verified	neighbourhood	neighbourhood_cleansed	neighbourhood_group_cleansed	latitude	longitude	property_type	room_type	accommodates	bathrooms	bathrooms_text	bedrooms	beds	amenities	price	minimum_nights	maximum_nights	minimum_minimum_nights	maximum_minimum_nights	minimum_maximum_nights	maximum_maximum_nights	minimum_nights_avg_ntm	maximum_nights_avg_ntm	calendar_updated	has_availability	availability_30	availability_60	availability_90	availability_365	calendar_last_scraped	number_of_reviews	number_of_reviews_ltm	number_of_reviews_l30d	first_review	last_review	review_scores_rating	review_scores_accuracy	review_scores_cleanliness	review_scores_checkin	review_scores_communication	review_scores_location	review_scores_value	license	instant_bookable	calculated_host_listings_count	calculated_host_listings_count_entire_homes	calculated_host_listings_count_private_rooms	reviews_per_month
0	17878	https://www.airbnb.com/rooms/17878	20231226034138	2023-12-27	city scrape	Condo in Rio de Janeiro · ★4.70 · 2 bedrooms · 2 beds · 1 bath	NaN	This is the one of the bests spots in Rio. Because of the large balcony and proximity to the beach, it has huge advantages in the current situation.	https://a0.muscache.com/pictures/65320518/30698f38_original.jpg	68997	https://www.airbnb.com/users/show/68997	Matthias	2010-01-08	Rio de Janeiro, Brazil	I am a journalist/writer. Lived in NYC for 15 years. I am now based in Rio and published 3 volumes of travel stories on AMAZ0N: "The World Is My Oyster". If you have never been to Rio, check out the first story, and you'll get an idea. Apart from Rio, you'll find 29 other travel stories from all around the globe.	within an hour	100%	96%	t	https://a0.muscache.com/im/pictures/user/67b13cea-8c11-49c0-a08d-7f42c330676e.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/67b13cea-8c11-49c0-a08d-7f42c330676e.jpg?aki_policy=profile_x_medium	Copacabana	2.0	5.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Copacabana	NaN	-22.96599	-43.17940	Entire condo	Entire home/apt	5	NaN	1 bath	NaN	2.0	[]	$1,357.00	5	28	5	5	28	28	5.0	28.0	NaN	t	5	7	14	269	2023-12-27	311	29	4	2010-07-15	2023-12-22	4.70	4.77	4.65	4.83	4.91	4.77	4.67	NaN	f	1	1	0	1.90
1	25026	https://www.airbnb.com/rooms/25026	20231226034138	2023-12-27	city scrape	Rental unit in Rio de Janeiro · ★4.72 · 1 bedroom · 1 bed · 1 bath	NaN	Copacabana is a lively neighborhood and the apartment is located very close to an area in Copa full of bars, cafes and restaurants at Rua Bolivar and Domingos Ferreira. Copacabana never sleeps, there is always movement and it's a great mix of all kinds of people.	https://a0.muscache.com/pictures/a745aa21-b8dd-4959-a040-eb8e6e6f07ee.jpg	102840	https://www.airbnb.com/users/show/102840	Viviane	2010-04-03	Rio de Janeiro, Brazil	Hi guys,\n\nViviane is a commercial photographer, an avid world traveler, (a former photographer for Airbnb) and an Airbnb superhost. And a free lance photographer for other wonderful clients. She loves life and meeting people.\n\nWe work together in providing the best accommodation to people and we are\nfirm believers of enjoying the moment as a prime attitude towards life!\n	within an hour	100%	80%	t	https://a0.muscache.com/im/pictures/user/315ddc81-bea3-4bf0-8fc7-be197a6541ff.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/315ddc81-bea3-4bf0-8fc7-be197a6541ff.jpg?aki_policy=profile_x_medium	Copacabana	1.0	5.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Copacabana	NaN	-22.97735	-43.19105	Entire rental unit	Entire home/apt	3	NaN	1 bath	NaN	1.0	[]	$865.00	2	60	2	4	60	60	2.2	60.0	NaN	t	3	18	48	228	2023-12-27	275	29	2	2010-06-07	2023-12-03	4.72	4.70	4.79	4.81	4.92	4.84	4.60	NaN	f	1	1	0	1.67
2	35764	https://www.airbnb.com/rooms/35764	20231226034138	2023-12-27	city scrape	Loft in Rio de Janeiro · ★4.90 · 1 bedroom · 1 bed · 1.5 baths	NaN	Our guests will experience living with a local peole "Carioca" in a very friendly building with 24 hours a day security with all kind of stores, banks, transports, restaurants.	https://a0.muscache.com/pictures/23782972/1d3e55b0_original.jpg	153691	https://www.airbnb.com/users/show/153691	Patricia Miranda & Paulo	2010-06-27	Rio de Janeiro, Brazil	Hello, We are Patricia Miranda and Paulo.\nWe are a couple who love to meet new people, new cultures, we both are very easy going persons, We are retired after working for several years in tourism and an international airline company. We also used do host in our own residence International students from all over the world. We are gay friendly and everybody is welcome! \n\n\n\n!	within an hour	100%	98%	t	https://a0.muscache.com/im/users/153691/profile_pic/1277774787/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/153691/profile_pic/1277774787/original.jpg?aki_policy=profile_x_medium	Copacabana	1.0	2.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Copacabana	NaN	-22.98107	-43.19136	Entire loft	Entire home/apt	2	NaN	1.5 baths	NaN	1.0	[]	$373.00	3	15	1	6	7	15	3.1	14.7	NaN	t	4	9	12	62	2023-12-27	454	36	2	2010-10-03	2023-12-17	4.90	4.93	4.93	4.97	4.95	4.94	4.89	NaN	f	1	1	0	2.82
3	41198	https://www.airbnb.com/rooms/41198	20231226034138	2023-12-27	city scrape	Rental unit in Rio de Janeiro · ★4.21 · 2 bedrooms · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/3576716/2d6a9301_original.jpg	178975	https://www.airbnb.com/users/show/178975	Nicky	2010-07-23	Rio de Janeiro, Brazil	Hi fellow Airbnb-ers,\r\nMr Francis , Nixx, Nicky ,Nick call me what you like\r\nOriginally from England but now in South America\r\nI love This crazy thing called life. I enjoy meeting interesting multi dimensional people from any country, class or colour ., \r\nI don't understand negative or petty people! because I believe life is just too short!\r\nI'm not the greatest tour guide, but it would be my pleasure to help you where I can.\r\nI administrate a few places on here, so feel free to take a browse of my listings.\r\nPlease remember that some of these places may be owners homes and not hotels,\r\nSo don't expect the hilton treatment as I like to keep it sweet & simple.\r\nLet me know also if the apt is different from what was listed and I will do my best to \r\nRectify the situation.\r\nRemember even though we are here to do a lil Bizniz the most important thing is to enjoy Rio de Janeiro in all it's splendour ! Rio is always an Experience!\r\nMy favourite travel hotspots outside of Brazil - Colombia or Caribbean \r\nHere is a story for you\r\nThere was a married American guy called Lance who was working abroad as a \r\ncomputer systems analyst to make ends meet.He traveled a lot for his job\r\nAnd had been doing so for the last 37 years. Last year whilst working in Thailand\r\nHe picked up a young sexy wife 23 years old she was and a real beauty! It was\r\nreally difficult for him to leave her at home, but the bills needed to be paid and \r\nbesides his wife was high maintenance.\r\n\r\nIn a particularly difficult month he received a message from his\r\nDesirable Wife who was taking care of his home" I signed up for a new service Airbnb\r\nWhere you can rent space in your house,make good money and I buy new\r\nShoes"\r\nHaving a beautiful home (and not to mention photo), it wasn't long before she received\r\nA guest, actually a handsome pilot from Greece, Adonis was his name.\r\n\r\n After 5 days Lance could hardly make contact with his wife but unexpectedly \r\n received a message from his Airbnb guest. :\r\n\r\nHi Sir,\r\nThank you, I enjoyed using your home & everything your city had to offer,\r\nI hope you won't be mad but\r\nI was using your wife...I was using day and night ...\r\nI explored immensely,\r\nI was using when you are not present at home... \r\nIn fact I was using more than You are using.....\r\n\r\nI confess this because now I feel very much guilt...\r\nAnd is not acceptable under the eyes of God\r\nHope You will accept my sincere apologies".\r\n\r\n... Lance distraught with this revelation , jumped On the next plane to his city, \r\n, entered his home tied & taped up his wife., and made her watch while he cut\r\nUp and burnt all her expensive clothes and shoes, put her in front of the mirror\r\nAnd proceeded to shear off her hair\r\n\r\nFew minutes later he received another message :\r\n\r\nSorry sir, spelling mistake ... wifi not wife.\r\n\r\n\r\n\r\n\r\n\r\nLol! \r\n\r\n\r\n	within an hour	90%	89%	f	https://a0.muscache.com/im/users/178975/profile_pic/1384245754/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/178975/profile_pic/1384245754/original.jpg?aki_policy=profile_x_medium	Copacabana	4.0	5.0	['email', 'phone']	t	t	NaN	Copacabana	NaN	-22.98102	-43.19172	Entire rental unit	Entire home/apt	5	NaN	1 bath	NaN	NaN	[]	$1,701.00	3	365	3	7	365	365	3.2	365.0	NaN	t	15	38	41	44	2023-12-27	17	0	0	2013-06-04	2016-02-09	4.21	3.88	4.25	4.69	4.56	4.44	4.38	NaN	f	2	2	0	0.13
4	326205	https://www.airbnb.com/rooms/326205	20231226034138	2023-12-27	city scrape	Condo in Rio de Janeiro · ★4.57 · 1 bedroom · 1 bed · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/c550151d-910c-40c6-96a8-d2a8bd770361.jpg	1603206	https://www.airbnb.com/users/show/1603206	Bob	2012-01-13	Rio de Janeiro, Brazil	I'm originally from the US, but moved to this Great City of\n Rio de Janeiro.	within a few hours	100%	93%	f	https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/d9351e88-fd2a-42b7-9c7a-1eb3caffd888.jpg?aki_policy=profile_x_medium	Copacabana	7.0	7.0	['email', 'phone']	t	f	NaN	Copacabana	NaN	-22.96825	-43.18237	Entire condo	Entire home/apt	4	NaN	1 bath	NaN	1.0	[]	$366.00	3	180	3	3	180	180	3.0	180.0	NaN	t	6	22	27	293	2023-12-27	152	14	0	2012-04-18	2023-11-21	4.57	4.72	4.46	4.83	4.77	4.83	4.59	NaN	f	5	5	0	1.07
5	326575	https://www.airbnb.com/rooms/326575	20231226034138	2023-12-27	city scrape	Rental unit in Rio de Janeiro · ★4.81 · 2 bedrooms · 3 beds · 2 baths	NaN	Come to stay in Baixo Copa, the more trendy and happy neighborhood of all Rio de Janeiro, in the heart of Copacabana, less than a half block from the beach. Restaurants, bars, grocery stores, theaters, banks, hotels and tourism agencies are in the neighborhood.	https://a0.muscache.com/pictures/4cffcbcf-16c2-4624-afee-29a7ffe20698.jpg	1668565	https://www.airbnb.com/users/show/1668565	Maria José	2012-01-29	Rio de Janeiro, Brazil	My name is Maria José, born in 1977 in Brazil. \n\nHoping to meet you,\n\nMaria José	within a few hours	100%	69%	t	https://a0.muscache.com/im/pictures/user/f52d7397-5f15-4876-a275-bc0ad10c9cb8.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/f52d7397-5f15-4876-a275-bc0ad10c9cb8.jpg?aki_policy=profile_x_medium	Copacabana	1.0	8.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Copacabana	NaN	-22.97696	-43.18933	Entire rental unit	Entire home/apt	5	NaN	2 baths	NaN	3.0	[]	$368.00	4	60	4	4	60	60	4.0	60.0	NaN	t	4	9	39	245	2023-12-27	227	12	0	2012-03-19	2023-11-21	4.81	4.85	4.80	4.91	4.89	4.95	4.73	NaN	f	1	1	0	1.58
6	216461	https://www.airbnb.com/rooms/216461	20231226034138	2023-12-26	city scrape	Rental unit in Rio de Janeiro · 1 bedroom · 1 bed · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/2628485/1ed768bb_original.jpg	1154263	https://www.airbnb.com/users/show/1154263	Zeilma , Da	2011-09-13	Rio de Janeiro, Brazil	Olá meu nome é Zeilma, moro no Rio de Janeiro. Sou casada, não tenho filhos. Será um prazer receber a sua visita!	a few days or more	0%	NaN	f	https://a0.muscache.com/im/users/1154263/profile_pic/1336700167/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/1154263/profile_pic/1336700167/original.jpg?aki_policy=profile_x_medium	Flamengo	1.0	1.0	['email', 'phone']	t	t	NaN	Flamengo	NaN	-22.93990	-43.17676	Private room in rental unit	Private room	2	NaN	1 bath	NaN	1.0	[]	$734.00	1	760	1	1	760	760	1.0	760.0	NaN	t	30	60	90	365	2023-12-26	0	0	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	f	1	0	1	NaN
7	48305	https://www.airbnb.com/rooms/48305	20231226034138	2023-12-26	city scrape	Rental unit in Ipanema · ★4.76 · 6 bedrooms · 7 beds · 7 baths	NaN	Enter Bossa Nova history by staying in the very street where real-life 'Girl From Ipanema' inspired Vinicius de Moraes to write the worldwide famous song, "each day when she walks to the sea".<br /><br />Located seconds from Ipanema Beach's best spot Posto 9, on the first beach block in the heart of Ipanema’s very best neighbourhood, enjoy staying in this elegant and modern hideaway in a peaceful residential street.<br /><br />Ipanema and Leblon are by far the safest locations in Rio, with popular restaurants, cafes and boutique stores walking distance to the apartment.	https://a0.muscache.com/pictures/miso/Hosting-48305/original/cce14bf9-c5b6-44c6-a89f-61323975afdb.jpeg	70933	https://www.airbnb.com/users/show/70933	Goitaca	2010-01-16	Rio de Janeiro, Brazil	A new frontier of hospitality\n\nThe word meaning ‘Nomad’ in the native language of Tupi Guarani, Goitaca symbolizes a new genre of travel, one built with the modern traveler in mind. With locally-rooted and experience-driven stays in homes that are intentionally designed, fully-equipped, and remote-work ready, we’re driven to shift the role of hospitality in the world. Bringing the comfort of a hotel together with the privacy of a home, our residences and customized care provide unique experiences for our guests. \n\nExperience-driven stays that nurture our guests’ well-being \n\nThe well-being and satisfaction of our guests are our utmost focus and we are determined to continue improving the quality and depth of the experiences and stories we’re creating. We believe in delivering remarkable hospitality that is also accessible. By designing, developing, and operating our residences ourselves, we provide unique, personalized stays at a fraction of the cost and pass those savings back to our guests.\n\nA tribute to Brazil\n\nOur wish is that our guests may discover and experience the magic, beauty, and *alegria* of Rio, while paying homage to its history and multi-faceted culture.\n\nBehind Goitaca stands a small and dedicated local team who take pride in going the extra mile to ensure our guests live an easy, authentic, and unforgettable Rio story. Working together since 2011, we have been lucky to welcome over 2,000 guests and continue to connect and learn from them.	within a few hours	100%	96%	t	https://a0.muscache.com/im/pictures/user/c2d77835-fab6-45f9-a3ef-ef570dda44a5.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/c2d77835-fab6-45f9-a3ef-ef570dda44a5.jpg?aki_policy=profile_x_medium	Ipanema	12.0	33.0	['email', 'phone', 'work_email']	t	t	Ipanema, Rio de Janeiro, Brazil	Ipanema	NaN	-22.98591	-43.20302	Entire rental unit	Entire home/apt	13	NaN	7 baths	NaN	7.0	[]	$6,604.00	2	89	2	5	89	89	2.3	89.0	NaN	t	18	38	65	319	2023-12-26	163	36	3	2011-03-02	2023-12-10	4.76	4.72	4.70	4.83	4.83	4.94	4.59	NaN	t	10	9	1	1.04
8	216700	https://www.airbnb.com/rooms/216700	20231226034138	2023-12-28	city scrape	Rental unit in Rio de Janeiro · ★4.96 · 1 bedroom · 1 bed · 1 shared bath	NaN	O bairro de Laranjeiras é bem residencial e arborizado. Fica na Zona Sul do Rio de Janeiro, bem próximo das praias e do Centro da cidade. Na principal rua do bairro, Rua das Laranjeiras, tem ônibus que leva aos principais bairros da cidade e muito pontos turísticos. A minha rua fica distante 20 minutos a pé da estação do metro Largo do Machado. Vocês podem ir andando, 10 minutos, para a estação do trem do Corcovado que leva ao Cristo Redentor. A minha rua, Rua General Glicério, é a rua mais linda do bairro e fica em um recanto que parece uma bairro dentro do bairro. É uma rua bem segura e aos sábados tem feira livre com música ao vivo na praça. Em frente ao meu prédio tem padaria, pequenos restaurante e mini-mercados. Na rua principal, esquina com a minha rua tem bancos, supermercados, farmácias, pontos de taxi e todos os outros serviços.	https://a0.muscache.com/pictures/6162310/be07750f_original.jpg	1118486	https://www.airbnb.com/users/show/1118486	Moara	2011-09-06	Rio de Janeiro, Brazil	Sou formada em Engenharia na UFRJ, Analise de Sistemas na PUC e trabalhei 20 anos com Marketing.\r\nMeu marido é musico e compositor. Atualmente estou trabalhando como empresaria e produtora cultural e o resultado principal desse trabalho foi o lançamento do primeiro CD do meu marido.\r\nTrabalho também com consultoria na área de marketing e adoro fotografia.\r\nTenho uma filha cineasta e um filho jornalista, que moram sozinhos, e o meu filho mais jovem ainda vive comigo e meu marido.\r\nAdoramos curtir os amigos, cinema, teatro, shows, etc	within a few hours	90%	100%	f	https://a0.muscache.com/im/users/1118486/profile_pic/1338861150/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/1118486/profile_pic/1338861150/original.jpg?aki_policy=profile_x_medium	Laranjeiras	3.0	5.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Laranjeiras	NaN	-22.94373	-43.19147	Private room in rental unit	Private room	4	NaN	1 shared bath	NaN	1.0	[]	$300.00	3	30	3	3	30	30	3.0	30.0	NaN	t	24	51	81	356	2023-12-28	24	3	0	2012-06-18	2023-11-05	4.96	4.91	4.86	5.00	5.00	4.91	4.77	NaN	f	2	0	2	0.17
9	219250	https://www.airbnb.com/rooms/219250	20231226034138	2023-12-26	city scrape	Loft in Rio de Janeiro · ★4.82 · 1 bedroom · 2 beds · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/60226390/d079690d_original.jpg	1134264	https://www.airbnb.com/users/show/1134264	Ricardo	2011-09-09	Rio de Janeiro, Brazil	Sou designer e, desenvolvo pesquisas na área de construção de embarcações artesanais. Sou casado e minha companheira se chama Rachel. Para mim é sempre um prazer receber pessoas em minha casa, pois trocamos experiências e ampliamos a nossa rede de amigos.	within an hour	100%	100%	t	https://a0.muscache.com/im/pictures/user/2ab75f2d-15d0-4d01-a565-4d1483fed334.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/2ab75f2d-15d0-4d01-a565-4d1483fed334.jpg?aki_policy=profile_x_medium	Santa Teresa	2.0	2.0	['email', 'phone', 'work_email']	t	t	NaN	Santa Teresa	NaN	-22.91666	-43.17947	Entire loft	Entire home/apt	4	NaN	1 bath	NaN	2.0	[]	$254.00	2	30	2	5	1125	1125	2.1	1125.0	NaN	t	5	9	37	312	2023-12-26	431	25	2	2012-06-11	2023-12-11	4.82	4.87	4.74	4.94	4.87	4.76	4.78	NaN	t	2	2	0	3.07

	id	listing_url	scrape_id	last_scraped	source	name	description	neighborhood_overview	picture_url	host_id	host_url	host_name	host_since	host_location	host_about	host_response_time	host_response_rate	host_acceptance_rate	host_is_superhost	host_thumbnail_url	host_picture_url	host_neighbourhood	host_listings_count	host_total_listings_count	host_verifications	host_has_profile_pic	host_identity_verified	neighbourhood	neighbourhood_cleansed	neighbourhood_group_cleansed	latitude	longitude	property_type	room_type	accommodates	bathrooms	bathrooms_text	bedrooms	beds	amenities	price	minimum_nights	maximum_nights	minimum_minimum_nights	maximum_minimum_nights	minimum_maximum_nights	maximum_maximum_nights	minimum_nights_avg_ntm	maximum_nights_avg_ntm	calendar_updated	has_availability	availability_30	availability_60	availability_90	availability_365	calendar_last_scraped	number_of_reviews	number_of_reviews_ltm	number_of_reviews_l30d	first_review	last_review	review_scores_rating	review_scores_accuracy	review_scores_cleanliness	review_scores_checkin	review_scores_communication	review_scores_location	review_scores_value	license	instant_bookable	calculated_host_listings_count	calculated_host_listings_count_entire_homes	calculated_host_listings_count_private_rooms	reviews_per_month
90	97636	https://www.airbnb.com/rooms/97636	20231226034138	2023-12-28	city scrape	Home in Rio de Janeiro · ★4.62 · 1 bedroom · 2 beds · 1 shared bath	NaN	NaN	https://a0.muscache.com/pictures/12339607/212f6773_original.jpg	496656	https://www.airbnb.com/users/show/496656	Marcia Longras	2011-04-09	Rio de Janeiro, Brazil	I'm a Brazilian lady, I was born in Rio de Janeiro, the wonderful city!\n I like to dance , travel, walk..\nI love to host!\r\nI enjoy Airbnb.\r\n\r\n Marcia Longras .	within an hour	100%	78%	f	https://a0.muscache.com/im/pictures/user/User-496656/original/ef187b44-0111-45bc-acf4-ac05479390a2.jpeg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/User-496656/original/ef187b44-0111-45bc-acf4-ac05479390a2.jpeg?aki_policy=profile_x_medium	Botafogo	6.0	13.0	['email', 'phone']	t	t	NaN	Botafogo	NaN	-22.94169	-43.18703	Private room in home	Private room	2	NaN	1 shared bath	NaN	2.0	[]	$540.00	78	520	78	78	520	520	78.0	520.0	NaN	t	30	60	90	365	2023-12-28	17	0	0	2012-01-04	2021-12-15	4.62	4.43	4.36	4.86	4.79	4.43	4.29	NaN	f	6	3	3	0.12
91	272631	https://www.airbnb.com/rooms/272631	20231226034138	2023-12-27	city scrape	Rental unit in Rio de Janeiro · ★5.0 · 1 bedroom · 2 beds · 1 shared bath	NaN	NaN	https://a0.muscache.com/pictures/airflow/Hosting-272631/original/75b64c26-29b7-4e46-b9d0-c9f3cf6bcb86.jpg	1426830	https://www.airbnb.com/users/show/1426830	Neyde	2011-11-20	Rio de Janeiro, Brazil	SOU PROFESSORA DE HISTÓRIA. \r\nADORO MÚSICA E LIVROS. GOSTO MUITO DE VIAJAR E DE PREPARAR E SABOREAR BONS PRATOS.\r\n\r\nOBS. Falamos um pouco de inglês e francês	within a few hours	90%	95%	f	https://a0.muscache.com/im/pictures/user/63796636-be5f-4527-ac48-aee836bd6dbb.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/63796636-be5f-4527-ac48-aee836bd6dbb.jpg?aki_policy=profile_x_medium	Copacabana	4.0	7.0	['email', 'phone']	t	t	NaN	Copacabana	NaN	-22.96750	-43.18666	Private room in rental unit	Private room	2	NaN	1 shared bath	NaN	2.0	[]	$729.00	2	30	2	2	1125	1125	2.0	1125.0	NaN	t	24	54	84	264	2023-12-27	29	4	0	2014-07-01	2023-11-05	5.00	5.00	4.93	4.93	5.00	4.97	4.97	NaN	t	3	1	2	0.25
92	273261	https://www.airbnb.com/rooms/273261	20231226034138	2023-12-26	city scrape	Rental unit in Rio de Janeiro · 3 bedrooms · 3 beds · 3.5 baths	NaN	NaN	https://a0.muscache.com/pictures/4487816/a8d428ee_original.jpg	533566	https://www.airbnb.com/users/show/533566	Lucas	2011-04-25	Rio de Janeiro, Brazil	Hello , my name is Lucas , I'm a independent computer artist . I have this amazing apartment at wonderful city , Rio de Janeiro .	within a few hours	100%	NaN	f	https://a0.muscache.com/im/pictures/user/25dc6f05-635d-45b9-b4c1-87fb8e2252a4.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/25dc6f05-635d-45b9-b4c1-87fb8e2252a4.jpg?aki_policy=profile_x_medium	Leblon	1.0	2.0	['email', 'phone']	t	f	NaN	Leblon	NaN	-22.98632	-43.22936	Entire rental unit	Entire home/apt	6	NaN	3.5 baths	NaN	3.0	[]	$4,892.00	2	7	2	2	7	7	2.0	7.0	NaN	t	30	60	90	365	2023-12-26	0	0	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	f	1	1	0	NaN
93	400326	https://www.airbnb.com/rooms/400326	20231226034138	2023-12-27	city scrape	Rental unit in Rio de Janeiro · ★4.29 · 2 bedrooms · 4 beds · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/miso/Hosting-400326/original/2d72c30d-a810-4a03-bc3e-ed444ff1a41e.jpeg	1998370	https://www.airbnb.com/users/show/1998370	Jean	2012-03-24	Rio de Janeiro, Brazil	I am a young Brazilian who loves to travel and learning about new cultures.\r\nI know many places in Brazil and I have been traveling through out South America, United States, Canada, Australia and many other places\r\nAs I do not do this every day, I feel very happy to receive people in my town who are going through this experience!\r\n\r\nBased on my experiences around the planet, I just better prepared this apartment in Copacabana point to ensure the success and happiness of the people who come to visit Rio de Janeiro spend a good time!\r\n\r\nPlease feel free to get in touch, I'm more than happy to discuss any travel plans you may Possible have in the locality.\r\nYou are more than welcome already!\r\n\r\n\r\n\r\n"It was very great to stay stay some nights at Cool & Cozy Appartment! It was really nice and the location was the best at in Rio! I liked most Copacobana with its beach, small stores and eating-drinking possibilities. Everything was easy and very comfortable." \r\nVivika\r\n\r\n"El departamento está en una excelente ubicación! todo a la mano, cerca del subte, de la playa y con muchos colectivos sobre Barata Riveiro!!"\r\nKarina\r\n\r\nExcelente ubicacion del apartamento, acceso a mercados, tiendas, bares. Apartamento comodisimo, acogedor, limpio, una experiencia gratificante...\r\nNataly	within a few hours	90%	57%	NaN	https://a0.muscache.com/im/pictures/user/66ea20d2-7b42-45c3-ade1-ec3593460f92.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/66ea20d2-7b42-45c3-ade1-ec3593460f92.jpg?aki_policy=profile_x_medium	Copacabana	8.0	8.0	['email', 'phone']	t	t	NaN	Copacabana	NaN	-22.96714	-43.18372	Entire rental unit	Entire home/apt	6	NaN	1 bath	NaN	4.0	[]	$1,383.00	1	90	1	1	90	90	1.0	90.0	NaN	t	2	24	54	329	2023-12-27	155	1	0	2012-05-13	2023-08-26	4.29	4.25	4.01	4.75	4.76	4.86	4.19	NaN	f	5	5	0	1.10
94	98969	https://www.airbnb.com/rooms/98969	20231226034138	2023-12-26	city scrape	Home in Rio de Janeiro · ★4.79 · 1 bedroom · 2 beds · 1.5 baths	NaN	NaN	https://a0.muscache.com/pictures/airflow/Hosting-98969/original/54f1c924-6822-4c61-a93b-2160e0cd91b4.jpg	521613	https://www.airbnb.com/users/show/521613	Cyro	2011-04-19	Rio de Janeiro, Brazil	Ola , meu nome é Cyro e tenho ótimos espaços para alugar na cidade maravilhosa do Rio de Janeiro ,venha conhecer !	within an hour	100%	91%	f	https://a0.muscache.com/im/users/521613/profile_pic/1303253512/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/521613/profile_pic/1303253512/original.jpg?aki_policy=profile_x_medium	Recreio dos Bandeirantes	5.0	5.0	['email', 'phone']	t	f	NaN	Recreio dos Bandeirantes	NaN	-23.03154	-43.47437	Private room in home	Private room	2	NaN	1.5 baths	NaN	2.0	[]	$267.00	2	30	2	2	30	30	2.0	30.0	NaN	t	22	37	67	157	2023-12-26	48	24	2	2012-01-18	2023-12-17	4.79	4.73	4.48	4.85	4.96	4.94	4.79	NaN	f	4	1	3	0.33
95	404674	https://www.airbnb.com/rooms/404674	20231226034138	2023-12-27	previous scrape	Rental unit in Rio de Janeiro · ★4.87 · 1 bedroom · 3 beds · 2.5 shared baths	NaN	NaN	https://a0.muscache.com/pictures/4946952/f1288650_original.jpg	261954	https://www.airbnb.com/users/show/261954	Elisa	2010-10-14	Rio de Janeiro, Brazil	We're a very, VERY happy and mix couple: half from Buenos Aires, Argentina, and half (may be the best one!) from Rio de Janeiro. This is the city that we choose for live on it! I'm a spanish teacher and my husband, Marcelo, is a musician, a flute player. So, it's easy to imagine that music (the good one, of any style) is a very important part of our routines! \n\nOur interests are traveling, cinema and good music!\n\nWe love to make new friends and to know different cultures. \n\nStay with us…and feel so welcome at our nest! We hope to have you here at our place!!! :-)	within a few hours	100%	67%	f	https://a0.muscache.com/im/pictures/user/2b48ea47-c47f-460c-8a89-50f452a2a9ba.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/2b48ea47-c47f-460c-8a89-50f452a2a9ba.jpg?aki_policy=profile_x_medium	Flamengo	3.0	3.0	['email', 'phone', 'work_email']	t	f	NaN	Flamengo	NaN	-22.93974	-43.17496	Private room in rental unit	Private room	3	NaN	2.5 shared baths	NaN	3.0	[]	$306.00	30	90	30	30	90	90	30.0	90.0	NaN	t	2	7	30	30	2023-12-27	115	0	0	2012-05-11	2017-03-02	4.87	4.87	4.90	4.90	4.98	4.83	4.79	NaN	f	3	1	2	0.81
96	273333	https://www.airbnb.com/rooms/273333	20231226034138	2023-12-28	city scrape	Guest suite in Rio de Janeiro · ★4.86 · 1 bedroom · 1 bed · 1 private bath	NaN	O Jardim Botânico é um bairro lindo! Fica entre a Floresta da Tijuca, maior floresta urbana do mundo, e a Lagoa Rodrigo de Freitas. A suite está localizada a um quarteirão do parque do Jardim Botânico, que é um passeio maravilhoso e a 2 quarteirões da Lagoa. Chegando na Lagoa tem-se uma vista linda, que vai mudando conforme se dá a volta nela, a volta completa tem 7,5 km. Caminhando pela Lagoa chega-se a Ipanema, pra um banho de mar, em meia hora! E a noite, na Lagoa, tem várias opções de bares e restaurantes. No Jardim Botânico tem supermercado, farmácia, banco, correio, loja, padaria, etc... Fora todos os bares, restaurantes e lugares deliciosos pra café da manhã. E ainda tem muito verde! Com 40 minutos de caminhada pode-se tomar um banho de cachoeira no meio da Floresta da Tijuca, é de tirar o fôlego!	https://a0.muscache.com/pictures/3200821/8fd48336_original.jpg	625565	https://www.airbnb.com/users/show/625565	Kakau	2011-05-25	Rio de Janeiro, Brazil	Sou pintora e designer, morei 9 anos na Europa e atualmente vivo no Rio, fonte de inspiração para minha arte. Pinto a cidade maravilhosa e assino uma linha de produtos inspirada em suas cores, relevos e calçadas.\nMoro no Jardim Botânico, um dos bairros mais charmosos do Rio, colado na Floresta da Tijuca, a 2 quarteirões da Lagoa Rodrigo de Freitas, logo em baixo do sovaco do Cristo.\nAs suites que alugo são independentes com privacidade total.	within a few hours	90%	56%	f	https://a0.muscache.com/im/users/625565/profile_pic/1306358577/original.jpg?aki_policy=profile_small	https://a0.muscache.com/im/users/625565/profile_pic/1306358577/original.jpg?aki_policy=profile_x_medium	Jardin Botânico	2.0	3.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Jardim Botânico	NaN	-22.96612	-43.21899	Private room in guest suite	Private room	2	NaN	1 private bath	NaN	1.0	[]	$193.00	3	1125	3	3	1125	1125	3.0	1125.0	NaN	t	0	0	0	240	2023-12-28	24	0	0	2012-01-06	2022-04-04	4.86	4.83	4.71	5.00	5.00	4.74	4.45	NaN	f	2	0	2	0.16
97	99547	https://www.airbnb.com/rooms/99547	20231226034138	2023-12-26	city scrape	Rental unit in Rio de Janeiro · ★4.58 · Studio · 2 beds · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/01c55423-2959-426f-a476-cbd1bab93d98.jpg	524101	https://www.airbnb.com/users/show/524101	Fabiana	2011-04-20	Rio de Janeiro, Brazil	NaN	within a day	100%	88%	f	https://a0.muscache.com/im/pictures/user/e9fb3c93-c035-401f-bb5a-b5dcc9f19381.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/e9fb3c93-c035-401f-bb5a-b5dcc9f19381.jpg?aki_policy=profile_x_medium	Lapa	2.0	31.0	['email', 'phone']	t	t	NaN	Santa Teresa	NaN	-22.91491	-43.18296	Entire rental unit	Entire home/apt	3	NaN	1 bath	NaN	2.0	[]	$381.00	2	89	3	3	1125	1125	3.0	1125.0	NaN	t	30	54	84	174	2023-12-26	66	3	0	2013-03-10	2023-11-06	4.58	4.75	4.66	4.84	4.83	4.70	4.56	NaN	t	1	1	0	0.50
98	99971	https://www.airbnb.com/rooms/99971	20231226034138	2023-12-28	city scrape	Loft in Rio de Janeiro · ★4.79 · Studio · 3 beds · 1 bath	NaN	NaN	https://a0.muscache.com/pictures/670706/0f35611d_original.jpg	525976	https://www.airbnb.com/users/show/525976	Ricardo	2011-04-21	NaN	I am an independent professional from Rio de Janeiro, Brazil, working and living in many different parts of the globe\r\nSou um profissional autônomo, viajo muito pelo mundo a trabalho, sou carioca e visito sempre o Rio.	within an hour	90%	100%	t	https://a0.muscache.com/im/pictures/user/2a1db51e-0495-4fef-8500-c6494406669e.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/2a1db51e-0495-4fef-8500-c6494406669e.jpg?aki_policy=profile_x_medium	Vidigal	1.0	3.0	['email', 'phone', 'work_email']	t	t	NaN	Leblon	NaN	-22.98812	-43.22897	Entire loft	Entire home/apt	5	NaN	1 bath	NaN	3.0	[]	$446.00	3	1125	3	5	1125	1125	3.0	1125.0	NaN	t	4	15	34	268	2023-12-28	157	22	1	2011-08-09	2023-12-01	4.79	4.72	4.66	4.88	4.88	4.57	4.68	NaN	f	1	1	0	1.04
99	273363	https://www.airbnb.com/rooms/273363	20231226034138	2023-12-26	city scrape	Home in Rio de Janeiro · ★5.0 · 1 bedroom · 1 bed · 1 private bath	NaN	Santa Teresa é um lugar único e muito interessante no Rio de Janeiro. Está situada na região central e no alto de uma colina oferecendo uma vista privilegiada da cidade, da Baia de Guanabara e do Pāo de Açúcar. Este bairro parece ter parado no tempo, com as suas casas antigas, palacetes, ruas estreitas com paralelepípedos e o famoso bondinho que leva os moradores e turistas ladeira abaixo.	https://a0.muscache.com/pictures/miso/Hosting-273363/original/af4b87af-1eac-4200-87de-7c8d6cceab52.jpeg	556738	https://www.airbnb.com/users/show/556738	Casa Da Carmen E	2011-05-04	Rio de Janeiro, Brazil	Somos um casal, Carmen e Fernando, ,que desde 1998 compartilhamos a nossa casa localizada em Santa Teresa, próximo ao Largo do Curvelo. Priorizamos a empatia e o respeito às diferenças! Como cariocas sentimos felicidade em divulgar a vida cultural e sugerir passeios na cidade. A casa possui um terraço com uma pequena piscina e uma vista panorâmica do centro da cidade e da Baía de Guanabara. Os quartos possuem cama de solteiro ou cama de casal, banheiro privativo, além de uma cozinha totalmente equipada para uso exclusivo dos moradores. Estão incluídos nos serviços oferecidos a internet wi-fi! É fácil chegar na casa, que está localizada a 4Km do Aeroporto Santos Dumont(vôos domésticos) com conexão de ônibus para o aeroporto Internacional (20 Km) e a 7Km do terminal interestadual de ônibus. Além disso, estamos a 10 minutos caminhando até a Lapa, bairro da boemia carioca, com vários opções de música e restaurantes, e a 10 minutos a pé da estação Glória do Metrô, de onde é possível chegar em Copacabana e Ipanema em 15 minutos. Próximo a casa, temos supermercado, restaurantes, farmácia e banco 24 horas. Ficaremos muito felizes em recebê-lo(a).	within a few hours	100%	25%	f	https://a0.muscache.com/im/pictures/user/694631f0-c779-476f-a57b-b08b7c14a53d.jpg?aki_policy=profile_small	https://a0.muscache.com/im/pictures/user/694631f0-c779-476f-a57b-b08b7c14a53d.jpg?aki_policy=profile_x_medium	Santa Teresa	5.0	6.0	['email', 'phone']	t	t	Rio de Janeiro, Brazil	Santa Teresa	NaN	-22.91825	-43.17872	Private room in home	Private room	1	NaN	1 private bath	NaN	1.0	[]	$60.00	30	1125	30	30	1125	1125	30.0	1125.0	NaN	t	0	0	0	269	2023-12-26	4	0	0	2015-03-11	2017-12-04	5.00	5.00	5.00	5.00	5.00	4.75	4.75	NaN	f	5	0	5	0.04

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